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1-20 of 30 items from 2015 « Prev | Next »
25 September 2015 9:01 AM, PDT | Us Weekly | See recent Us Weekly news »
He knows when to fold 'em. Country music legend Kenny Rogers announced his retirement during an interview on the Today show on Friday, Sept. 25. After six decades in the business and 76 albums, "The Gambler" crooner, 77, announced that he will do one last worldwide tour before hanging up his cowboy hat and boots. "I'm going to say goodbye at that point," Rogers, who has sold more than 120 million albums, told Today co-hosts Savannah Guthrie and Carson Daly. "I've done this long enough. I wrote [...] »
8 September 2015 9:46 AM, PDT | TVovermind.com | See recent TVovermind.com news »
Recently Frankie Muniz has suggested a Malcolm in the Middle "mid life crisis" reboot. Given all the reboots that have been sprouting up and the long-time cult following the show had, it's not a horrible ideas. Personally I think it's because Muniz has disappeared from the planet ever since the show ended. Even so, there are worse ideas out there. But that's not the story we're following today. In a stunning "Today I Learned" post on Reddit, it turns out if you check out Malcolm in the Middle's wikipedia page you see a tasty little nugget about the show. Turns out the show used mood-setting music in lieu of canned laughter. Artists used included Abba, They Might Be Giants, Kenny Rogers, Elo & the Getaway People. I personally wasn't a huge fan of the show but I will say this. If it weren't for »
- Nat Berman
6 September 2015 10:00 PM, PDT | Variety - Film News | See recent Variety - Film News news »
The first edition of the new Italian market, called Mia, will run Oct. 16-20 during the Rome Film Festival.
The market will be dedicated to feature films, TV series, documentaries and video games, and will be launching Make It With Italy, a co-production forum for international projects seeking an Italian minority co-production partner. The move is part of the mart's stated mission to make the Italian film industry more international.
Make It With Italy will be for films from outside Italy with elements that can have particular appeal for Italian producers to come on board as minority co-production partners. Projects must be budgeted at more than Euros 1.5 million, and have 30% of financing in place.
Mia topper Lucia Milazzotto (pictured) said that the idea is not to generate "exclusively financial co-productions." That said, "they don't all have to come shoot in Italy," she added. "But they should involve some »
- Nick Vivarelli
6 September 2015 10:00 PM, PDT | Variety - TV News | See recent Variety - TV News news »»
25 August 2015 10:49 PM, PDT | SoundOnSight | See recent SoundOnSight news »
Written by John Erick Dowdle & Drew Dowdle
Directed by John Erick Dowdle
How many foreign lives does it take to save a white American family? Thanks to the new chase-yarn, No Escape, we now have an answer. The guiltiest of guilty pleasures, director John Erick Dowdle has expertly crafted a taut action-thriller crammed with enough white privilege to make The Donald blush. Surprisingly, it's the intense performance of Owen Wilson that might allow you to curb your conscience and go along for the ride. It's undeniably fun… if you don't think about it too much.
Watching No Escape is a decidedly schizophrenic experience. On the one hand, John Erick Dowdle and his brother, Drew, have written an earnest script that takes its peril very seriously. All of the primary characters (who just happen to be Westerners) are constructed with the utmost care; giving each »
- J.R. Kinnard
10 July 2015 9:41 AM, PDT | ScreenDaily | See recent ScreenDaily news »
International audiovisual market Mia to to held during Rome Film Festival.
The Italian film and television industry has launched Mia, a new international market that will span cinema, TV, documentaries and videogames, to be held during the Rome Film Festival.
The first edition of Mia (Mercato Internazionale Audiovisivo, which translates as International Audiovisual Market) will run from October 16-20, 2015.
Associations involved in organising the market include for film, Anica (National Association of Cinema and Audiovisual Industries) and the Fondazione Cinema per Roma; for TV, including Agorà's activities, the Apt (Association of Television Producers); and for documentaries, the Doc/it association.
At a press conference today, it was revealed that Mia will offer film industry professionals networking opportunities, screenings, panels, lectures, workshops, co-production meetings, roundtables, as well as focuses on the latest market trends, on co-production and distribution at the global scale, paying particular attention to new platforms, transmedia storytelling and gaming with the participation of Aesvi »
- firstname.lastname@example.com (Michael Rosser)
9 July 2015 6:27 PM, PDT | Cinelinx | See recent Cinelinx news »
Come check out the latest trailer for Call of Duty: Black Ops 3 featuring zombies! Plus see all the cool collectors editions you can grab this Fall!
Today during San Diego Comic Con Treyarch and Activision revealed the latest edition to the zombie mode featured in Black Ops 3. The trailer does a good job of setting everything up and showing off some key game features.
The mode will be ready when the game launches on November 6th and the cast behind the characters include Jeff Goldblum, Heather Graham, Neal McDonough, Ron Perlman and Robert Picardo.
"Treyarch has crafted a totally unique and face-melting gameplay experience for our loyal Zombies community, with Call of Duty: Black Ops III: Zombies - Shadows of Evil" said Mark Lamia, Studio Head, Treyarch. "The development team has packed Shadows of Evil with more gameplay and fun than any other experience before it, and has an appropriately twisted and deep narrative, »
- firstname.lastname@example.com (Dustin Spino)
9 July 2015 9:14 AM, PDT | ScreenDaily | See recent ScreenDaily news »
Project supports new film talent from leading international film schools.
Giorgio Armani's Films of City Frames project has joined forces with the BFI London Film Festival for its second edition and will showcase titles to audiences at the festival in October.
Created in collaboration with Luxottica and Rai Cinema, the project involves promising students from a selection of international film schools, who will be asked to create a series of short films.
The schools for the second edition are:
Scuola Holden – TorinoAcademia Internacional de Cinema – São PauloSydney Film School – SydneySeoul Institute of the Arts – Seoul
Students will be given the task of making short films inspired by real lives – tales told through the eyes and emotions of characters filmed in the context of their daily lives.
Glasses from the Giorgio Armani Frames of Life collection will be the element that unites the stories, and will play a narrative role - not one that is purely aesthetic »
- firstname.lastname@example.com (Michael Rosser)
5 May 2015 8:19 AM, PDT | The Guardian - TV News | See recent The Guardian - TV News news »
Cilia Flores's quaint new show does little to improve President Nicolás Maduro's floundering image, as nation longs for telenovela heyday
Venezuela's first lady Cilia Flores has been drafted into the battle to reverse her husband's dismal approval ratings, but her dowdily wholesome new TV show looks more likely to reinforce perceptions that Chavismo is losing its charisma – as well as its audience.
The first edition of Flores's show – Con Cilia en Familia or With Cilia in the Family – featured the once-fiery lawyer in decidedly demure mode. "Blessings for all these beautiful children," she said as the cameras followed her around a paediatric hospital in the opening sequence. This was followed by a trip to an old people's home, then videotaped reminiscences with cabinet ministers about key moments in the history of the Bolivarian socialist revolution.
Related: Aló Presidente - episode 291: When Chávez reclaimed Las Malvinas
Continue reading. »
- Catalina Lobo-Guerrero in Caracas and Jonathan Watts
29 April 2015 2:34 PM, PDT | Slash Film | See recent Slash Film news »
Note from Editor Peter Sciretta: I've gotten a ton of e-mails, tweets and comments over the last month asking me what happened to Page 2. When I first started the column in February 2007, I never anticipated it would grow into what it would become. The first edition didn't even feature images, it was just […]
The post The Return of Page 2: Why We've Been Gone And Help Change The Future appeared first on /Film. »
- Peter Sciretta
28 April 2015 8:16 AM, PDT | SoundOnSight | See recent SoundOnSight news »
Every year E3, brings us the biggest gaming news of the year, as Microsoft, Sony and Nintendo drop their biggest announcements about upcoming games, release dates and new consoles. With the three day conference fast approaching, I figured it would be a good time to release my 2015 predictions. With so many recent developments happening over at Nintendo headquarters, I believe, there is reason to be optimistic about Nintendo's presence at the event this year – even, if the new Legend of Zelda game doesn't make an appearance. It's always hard to guess what Nintendo will announce since the company has always been so unpredictable, but I have high hopes for what could happen during Nintendo's live-stream presentation. So what surprises are in store this year? Here's my best guesses.
Note: This is a list of predictions, and not things we already know to expect such as »
- Ricky
27 April 2015 7:19 PM, PDT | TVLine.com | See recent TVLine.com news »
I wasn't planning on watching the Mayweather-Pacquiao boxing match this weekend — I'm more of a Kentucky Derby kinda guy, to be honest — but I can't imagine it being much bloodier than Top 8 Performance Night on The Voice.
Look, there's no denying that Season 8 of NBC's reality singing competition is as jam-packed with talent as Kim Kardashian's pencil skirts are heaving with badonkadonk. It's just that, with two more performers headed for a dinner date at The Rancor's basement apartment on Tuesday night, it seemed like nearly everyone was swinging hickory bats at melodies requiring butterfly-wing delicacy. »
13 April 2015 5:02 PM, PDT | Variety - Film News | See recent Variety - Film News news »
Film and TV producer Mark Gordon will be recognized with the Tom Sherak Award at the Fulfillment Fund's Stars 2015 benefit gala on October 14. The nonprofit is devoted to helping Los Angeles students overcome obstacles to achieve a college education. The 21st edition of the event will take place at the Beverly Hilton Hotel.
Gordon is the founder of Citizens of the World charter schools and the former chairman of Teach for America Los Angeles. He was honored in January with the PGA's Norman Lear Achievement Award. Gordon, who produced such films and TV shows as "Saving Private Ryan" and "Grey's Anatomy," recently launched an independent company with Entertainment One to finance and produce films and TV shows.
"Mark Gordon is an exemplary philanthropist in the world of education," said Fulfillment Fund CEO Kenny Rogers. "He is a fervent supporter of youth in Los Angeles who utilizes his »
- Variety Staff
1 April 2015 7:05 AM, PDT | ioncinema | See recent ioncinema news »
Everything old is new again. Berthed from the initial goal to both restore and digitize over 200+ films in Quebec's rich cinema of the past (e.g: Jean-Claude Lauzon's Léolo – see pic above), Quebecor's Éléphant ClassiQ is now moving into larger steel-trap memories of French film history and culture. I spoke to Gérald Duchaussoy, Project Manager for a new film fest initiative/event that'll take place in Montreal in mid November, one that serves up a plate of restored classic French films from France, Belgium, Switzerland, Africa and Quebec — all with English subtitles.
Eric Lavallée: Film preservation and restoration is a serious business and now we have several silent film festivals, Il Cinema Ritrovato, TCM, Grand Lyon joining the ranks Cannes Classics in serving a public need. I was wondering what kind of recent trends you've notice and what is your take on why this has »
- Eric Lavallee
29 March 2015 7:12 PM, PDT | Cinemaretro.com | See recent CinemaRetro news »
New film event
Éléphant ClassiQ: Movies that have marked the history of cinema In Montréal from November 19 to 22
Montréal, March 18, 2015 — Quebecor and Éléphant: The memory of Québec cinema are pleased to announce a new event: Éléphant ClassiQ, the only festival of its kind in Canada, will screen classic films from around the world on the big screen. Its theme will be les films qui ont fait le cinéma (movies that have marked the history of cinema).
The first edition of Éléphant ClassiQ was held last year as part of the Montreal Festival du nouveau cinéma. This year's edition will be held as a separate event on November 19, 20, 21 and 22, 2015 at three theatres: the Imperial Cinema, Salle Claude-Jutra at the Cinémathèque québécoise and Salle Pierre-Bourgault at Uqam. It will give film buffs an opportunity to experience great films of the past from Québec and elsewhere.
"Repertory films are a fabulous window on the past, »
- email@example.com (Cinema Retro)
25 March 2015 8:49 AM, PDT | Indiewire | See recent Indiewire news »
Read More: 5 Must-See New French Films From Rendez-Vous with French Cinema Quebecor and "Éléphant: The memory of Québec cinema" have announced a new event: Éléphant ClassiQ, which will screen classic films from around the world on the big screen. The first edition of Éléphant ClassiQ was held last year as a part of Montreal's "Festival du nouveau cinéma." This year, its theme will be, "les films qui ont fait le cinéma," or movies that have marked the history of cinema. The 2015 edition of Éléphant ClassiQ will feature films from the French-speaking world, and restored classic films from France, Belgium, Switzerland, Africa and Québec, which will be shown with English subtitles. The festival will also offer master classes and opportunities to meet distinguished people in the film industry. "Quebecor is proud to help bring our cinema to a wider audience," stated »
- Jena Keahon
23 March 2015 5:55 PM, PDT | Entertainment Tonight | See recent Entertainment Tonight news »
Gage Blackwell is fulfilling the dreams of so many as he got to sing with Dolly Parton!
The country artist sang some of her best ballads to the boy with down syndrome. The videos are posted on his Facebook page and are bringing smiles to more than just Gage.
When the 69-year-old singer first meets Gage, she jokes, "Is that Kenny Rogers? You look like Kenny Rogers! Did anybody ever tell you that?" She also gives him the nickname of Gage Rogers and sings her hit that she sang with Kenny, "Island in the Stream."
Post by Gage Blackwell.
Photos: Country Stars Then and Now
She sings "Ring of Fire," "9 to 5," "Coat of Many Colors" and "Jolene" to Gage as he knows all her songs.
Post by Gage Blackwell.
"We might be going on the road before you know it," Dolly says to the happy boy and then signs an autograph for him.
Post by Gage »
17 March 2015 5:49 AM, PDT | ScreenDaily | See recent ScreenDaily news »
European film funders warn EU from making "big bang" policy changes to copyright, authors call for fair remuneration
European film funders from 31 countries including the UK's BFI, Germany's Ffa and France's Cnc have warned the European Union (EU) to avoid making any "big bang" policy changes to copyright rules.
The Association of the European Film Agency Directors (EFADs) issued a resolution today (March 17) declaring that it considered the current EU copyright framework to be "fit for purpose" as "it provides a strong basis for current business models to evolve in response to people's changing preferences as to how they access films and other audiovisual works."
The film agency directors suggested that "the priority of the EU should be the establishment of a level playing field ensuring equel treatment between all operators, a commitment to economic sustainability and engagement in the creation of local works."
However, they stressed that "improving online cross-border access to European »
- email@example.com (Martin Blaney)
11 March 2015 | The Daily BLAM! | See recent The Daily BLAM! news »
Cocktail writer and historian David Wondrich presents the colorful, little-known history of classic American drinks–and the ultimate mixologist's guide–in this engaging homage to Jerry Thomas, father of the American bar. Wondrich reveals never-before-published details and stories about this larger-than-life nineteenth-century figure, along with definitive recipes for more than 100 punches, cocktails, sours, fizzes, toddies, slings, and other essential drinks, along with detailed historical and mixological notes. The first edition, published in 2007, won a James Beard Award. Now updated with newly discovered recipes and historical information, this new edition includes the origins of the first American drink, the Mint Julep (which Wondrich places before the American Revolution), and those »
- Pietro Filipponi
3 March 2015 7:43 AM, PST | Variety - Film News | See recent Variety - Film News news »
The Doha Film Institute has recruited a high-caliber roster of industry reps, including Toronto topper Cameron Bailey, Wild Bunch chief Vincent Maraval, and prominent British indie producer Mike Downey, for the imminent first edition of its Qumra event dedicated to fostering new Arab cinema which blends creative workshop, industry networking, and festival elements.
More than 100 industryites, some from leading European and Asian fests, including Cannes, Venice, Karlovy Vary, Locarno, Sarajevo and Busan are heading for Qumra, along with sales company execs from outfits including Elle Driver, Fortissimo Films, Memento Films, Wide, and Danny Glover's New York-based Louverture Films, repped by COO Joslyn Barnes. Also making the trek from New York will be Joana Vicente, head of the Independent Filmmmakers Project (Ifp).
The innovative shindig is named after the Arabic word "qumra," from which the word "camera" is believed to have originated.
As previously announced, Gael Garcia Bernal; Mauritanian director »
- Nick Vivarelli
1-20 of 30 items from 2015 « Prev | Next »
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text:
Wide Angle
A photographic view of the Appleby Horse Fair 2010
de Iain Francis and Marion Pope
A photographer's view of the 2010 horse fair. It includes images taken in the river and portraits of a few of the characters that make it such a unique event.
Comentario publicado.
o cree una cuenta para publicar un comentario.
Sitios de Blurb

subset: commoncrawl


text:
|Publication number
|Publication type
|Application number
|Publication date
|Jun 12, 2003
|Filing date
|Oct 8, 2002
|Priority date
|Dec 6, 2001
|Also published as
|Publication number
|Oleg Golobrodsky, David Ronen
|Original Assignee
|Oleg Golobrodsky, David Ronen
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (5), Referenced by (17), Classifications (19), Legal Events (3)
|External Links: USPTO, USPTO Assignment, Espacenet
[0001] The present invention relates to methods of detecting any type of behavior of interest and of identifying fraudsters in telecommunication networks.
[0002] In a highly competitive market environment, survival of network providers relies mainly on the network's ability to offer constant innovation, variety, flexibility and quality in delivering new services and merchandise to millions of users worldwide. High-value services such as VoIP, content delivery, video-on-demand, e-commerce and electronic transactions, are carried out over Next Generation Networks, placing Telecom (Telco) & Service Providers at higher risk of fraudulent attack than ever before. Fraud includes various activities performed by individuals or a group making use of a network or networks in a way which is not authorized, approved or intended by the network, in order to gain undue profit or cause damage to the operator or a 3rd party.
[0003] As fraudulent activities in the field of computer and telecom networks are becoming increasingly frequent, their detection is becoming increasingly important. Telecommunications fraud poses an annual multi-billion dollar problem to Telcos and Service Providers alike. International scams of a highly sophisticated technological nature have recently been associated with organized crime, cleverly employing self-educated fraud techniques and the assistance of hacking specialists. Once fraudsters find a weakness in the Telco/Service Provider environment, they will quickly and aggressively exploit it. Organized criminals and other intruders expect the breach to be eventually discovered, and therefore employ all means available to maximize their revenues as quickly as possible.
[0004] Telcos & Service Providers demand an adequate means for protecting their networks, resources and services.
[0005] Fraud Management is primarily concerned with the possibility to detect and prevent fraudulent activities causing constant painful losses. An effective fraud management solution must be powerful and flexible, easily adapted to changing environments, and support the rapid introduction of new services, advanced billing schemes & new network technologies. A powerful and complete fraud analysis solution includes various systems and tools that provide detection, investigation, and recording of fraudulent and malicious activities in the network. These enable the service provider to take subsequent actions while preventing the activities that inflict the most (financial) damage, and assisting the prosecution of fraudsters. Various fraud detection components are available to the Telcos & Service Providers.
[0006] Accordingly, various approaches exist for the fraud detection. The following are common approaches:
[0007] Threshold approach, being the most common form of quantitative analysis. In the threshold fraud detection, certain attributes of a user and the system behaviors are characterized in terms of counts, with some level established as permissible. The classic example of a threshold is a number of unsuccessful logins to a system. Heuristic threshold checks take the simple threshold detection a step further by adapting it to observed levels. This process increases the accuracy of the detection, especially when performing detection over a wide range of users or target environments. So, for instance, instead of having a detection rule triggering an alert when the number of failed logins exceeds three within an hour period, it is possible to create a detection rule that calculates an "abnormal" number of failed logins before alerting. The calculation may be done based on statistical formulas (such as the Gaussian function or a chi-square function) and a standard deviation model.
[0008] Neural networks. Neural networks use adaptive learning techniques to characterize any anomalous behavior. This non-parametric analysis technique (i.e., a numeral technique) operates on historical sets of training data. The network is considered a graph that consists of numerous simple processing elements called units that interact by using weighted connections. The knowledge of the net is encoded in the structure in terms of connections and their weights. Although training a net could be time-consuming, a trained neural net can speedily predict new cases. They can also be used in data mining applications for clustering, handwriting recognition, robot control. Output from the net is purely predictive. Since there is no descriptive component to a neural network model, a neural net's choice is hard to understand, and in fact, this technique is referred to as a "black box" technology. The key difference between neural networks and other techniques is that the neural networks are built from nodes having numerical coefficients and only operate directly on these numbers. As a result, any non-numeric data must be converted to numbers before one can use the data in the net.
[0009] Fraud analysis rules determine particular conditions as to which patterns or events in the network usage information (usage records) are considered suspicious and will generate alarms. The rules can define logical conditions that are built using a field (parameter) in a usage record against a particular value. A usage record contains information in the form of fields (parameters) about a service after the service is started to be delivered. For example, CDR (call details record) is a usage record of a telephone conversation. A condition "telephone conversation of a particular client is less than 30 sec" can be written down as "duration is <30 sec", where duration is a parameter, 30 sec is the value. The rules may also use ranges of values, lists of values (e.g., a so-called Hot destinations list, or a black list). For instance, alarms may be produced when a monetary transaction exceeds a certain amount or when a call is placed to specific destinations. Rules can define conditions or aggregated values over a specific period of time such as, for instance, the sum of duration of calls. Rules defined by the user may vary depending on a specific time period, so allowing the use of different rules during day, night, weekends, etc.
[0010] On the other hand, there is known a so-called Artificial Immune Model being a computational system based upon metaphors of natural immune systems. It comprises data manipulations, classification, reasoning and representation methodologies, that follow a plausible biological paradigm.
[0011] Likewise, Immune Engineering is a meta-synthesis process that uses the information contained in a problem itself to define a solution tool to the given problem, and then apply the solution tool to obtain a solution.
[0012] Some articles describe implementing Artificial Immune Model for preventing money transaction frauds [John Hunt et al. Immunizing against fraud IEE, Savoy place, London], and for Network intrusion detection [Jungwon Kim. An Artificial Immune System for Network Intrusion Detection; Jungwon Kim and Peter Bentley. An Artificial Immune Model for Network Intrusion Detection]. Both groups of the references relate to frauds in computer networks. In particular, an intrusion detection system (IDS) is defined as an automated system for the detection of computer system tampering. The main goal of an IDS is to detect unauthorized use, misuse and abuse of computer systems by both the system insiders and external intruders. Building of a network-based IDS is inspired by a human immune system, i.e., is based on so-called detectors (information blocks) known from the Artificial Immunity Model. The detectors are considered analogous to genes in real immune systems.
[0013] It should be emphasized that the problem of unauthorized intrusion significantly differs from problems of fraud in telecommunication networks, for example in next generation (combined) networks where fraud problems are much more complex.
[0014] The present invention proposes a method for detecting a behavior of a previously known type in surroundings including at least one telecommunication network, by using methods of Immune Engineering based on the Artificial Immune Model.
[0015] In particular, the invention proposes a method for detecting fraud or fraudulent behavior in such surroundings using approaches of Immune Engineering.
[0016] The proposed technique can be applied in a surrounding including at least one field from the following non-exhaustive list which comprises: Next Generation Networks, Internet, Voice/VoIP, and also in credit card and bank transactions, e-mail, and Calling Card services.
[0017] The central concept of the approach is as follows:
[0018] a method of detecting a behavior of interest in a surrounding including at least one of the above-mentioned fields, by using a data string characterizing the behavior of interest, the data string comprising data sub-strings characterizing fragments of the behavior of interest.
[0019] The method comprises general steps of:
[0020] analyzing the behavior of interest by obtaining a data string characterizing said behavior and called DNA, the data string comprising two or more data sub-strings characterizing fragments of the behavior of interest and called genes;
[0021] selecting two or more data fragments called detectors and being substantially close to said data sub-strings respectively;
[0022] applying said detectors to identify similar data fragments in newly incoming information concerning activity in the surrounding;
[0023] based on the identification results, judging whether the behavior of interest is detected in the newly incoming information.
[0024] According to the preferred version, the method is focused at
[0025] analyzing behavior of interest of a particular customer, by pre-building and further using the obtained data string characterizing behavior of interest of a particular customer, the data string comprising data sub-strings characterizing the behavior fragments of the customer. This method will be called a Fingerprinting method or technique.
[0026] Using terminology of the methods of Immune Engineering based on the Artificial Immunity Model, the sub-strings reflecting behavior fragments of the customer can metaphorically be compared to genes, and the characterizing data string formed from the sub-strings—to a DNA sequence.
[0027] We therefore will call the data string characterizing behavior of a customer as DNA of the customer, and the sub-strings of the DNA—as genes of the DNA.
[0028] However, according to another version, the method can be focused on detection of a specific type of fraud in the surrounding, and the method of analyzing behavior in the surrounding will be based on using a pre-built data string characterizing a fraudulent behavior of interest in the system (surrounding), the data string comprising one or more data sub-strings characterizing fragments of the fraudulent behavior of interest. The pre-built data string will be called a fraud DNA, wherein those one or more data sub-strings composing the fraud DNA will be called fraud genes. These fraud genes may be known in advance in the system (say, to an expert of the system), and the fraud DNA is usually pre-built directly from these fraud genes.
[0029] The above-described method will be further referred to as a fraud detection method.
[0030] Coming back to the fingerprinting method, the characterizing data string (DNA) should be first created which would reflect the behavior of interest of a customer.
[0031] The behavior of interest may be, for example, a regular or normal behavior which can be studied, say by a service provider in a telecommunication system for offering specific programs or discounts to the customers with such a behavior.
[0032] Of course, the focus of the fingerprinting method is placed on abnormal or fraudulent behavior of a customer that should be tracked after. For example, if such a behavior is noticed once, it can then be studied and formulated using the proposed method in order to catch a similar type of behavior in future and so prevent possible damages to a service provider.
[0033] To create the DNA, usage records reflecting the behavior of interest of the customer (usually, the archive "historic" usage records) can be pre-processed for obtaining there-from a number of genes in the form of data sub-strings, upon which the obtained genes can be composed into the characterizing data string like into a chain, using any separation marks. The genes may reflect, for example, a terminating telephone number used by the customer with a particular frequency, duration of calls of the customer, IP addresses and the frequency of their use, type of call (voice, fax, data), bandwidth characteristics of the calls, their start time, login strategy, etc.
[0034] For building the characterizing data string (DNA), weight coefficients can be used, associated with the sub-strings (genes).
[0035] The method of detecting the behavior of interest, upon creating the DNA, further comprises step (b) of selecting a set of one or more detectors, each being a data fragment relevant to the data string (DNA); the detectors being selected (i.e., are considered relevant) when each of them is substantially close to a particular gene of the DNA.
[0036] The criterion of "being substantially close" can be defined in various ways. For example, a first data sub-string of length L is considered substantially close to a second data sub-string of length L if the first one comprises "r" contiguous bits of the second one (where r is smaller than the length L). In such a case, the first data sub-string can be considered a detector relevant to the DNA comprising a gene being the first data sub-string. Of course, a detector is substantially close to a gene also if it completely coincides to the gene.
[0037] In the proposed process, selecting the detectors for the set can be provided in a number of ways, for example
[0038] by randomly generating data sub-strings of various lengths and comparing thereof with the pre-built DNA, more particularly with genes of the DNA to select among these sub-strings relevant detectors for the set;
[0039] by generating such data sub-strings which are substantially close to respective genes of the DNA (i.e., relevant in advance); this option also includes selecting detectors being simply equal to the genes.
[0040] Upon selecting the set of detectors relevant to DNA of the customer's behavior of interest (normal, or abnormal=fraudulent), a stage of studying the behavior of interest is terminated.
[0041] Now, the selected detectors can be applied to perform a so-called distributed analysis of newly incoming information representing activity of any client in said surrounding, thereby performing step (c) of analyzing behavior of customers in the surrounding (both for the technology of fingerprinting, and the technique of fraud detection).
[0042] For example, the detectors relevant to the DNA of the behavior of interest can be compared with incoming information contained in real time data bases of the surrounding (say, a telecommunication network), i.e. with fragments of a real time behavior of an arbitrary customer.
[0043] To do that, during a search in the real data bases, behavior of an arbitrary customer is checked from the point of presence in it such behavior fragments which are similar to the genes of the characterizing DNA; therefore such data sub-strings which may comprise said fragments are extracted from the real time data bases and further compared with the previously selected set of detectors.
[0044] For extracting the data sub-strings of interest from the real time data bases, first so-called aggregated usage records are built for a particular customer, and then the usage records are preprocessed similarly to the way the historic usage records were preprocessed for obtaining the genes of the DNA.
[0045] The information for obtaining the aggregated usage record with such sub-strings of interest can be found in a random bulk of data contained in real time data bases such as CDR—Call Detail Records.
[0046] Each real data behavior fragment can be identified to match to the search (i.e., considered to correspond to a suitable characterizing detector) with a probabilistic approach. For example, the before-mentioned method of any r-contiguous bits can be used for this purpose.
[0047] The data sub-string obtained from the real time data base, which matches to one or more detectors from the set of detectors, is taken into account for further consideration.
[0048] In other words, the distributed analysis of the incoming information comprises extracting fragments of said newly incoming information which fragments may be similar to the genes of said DNA, collecting and processing said fragments into aggregated usage records, and
[0049] applying said detectors by comparing the aggregated usage records with the selected detectors to determine a percent of detectors of the set matching to the fragments of said aggregated usage records.
[0050] When, for an arbitrary customer, one or more such fragments (data sub-strings) are found during any period of time selected for searching, and said data sub-strings in total (i.e., the aggregated usage records) match to a predetermined number or percentage of detectors from the selected set, wherein a critical percentage of the identified detectors in the set is estimated by a predetermined threshold,
[0051] behavior of this arbitrary customer is considered to match to the behavior of interest characterized by the DNA.
[0052] In other words, if a fraudster had been noticed in the past to behave with a fraud in this and/or other network, field or surrounding (and caught or not caught at that time), this fraudster can be identified and caught in future by the proposed fingerprinting technique, if he (she) tries to use the previously used technology of fraud. However, the fingerprinting can be successfully used for other purposes, say, for allocating one or more clients in a particular telecom network, having the pattern of behavior defined by the pre-built characterizing data string. In this case, the pre-built data string and data detectors characterize a special manner of behavior of an individual which is required to the provider for statistics, offering a new service, discounts, or the like purposes.
[0053] The fingerprinting can preferably be used as a technique for preventing fraud which does not involve immediate fraud detection, but enables:
[0054] pointing an unknown arbitrary customer as a probable fraudster due to similarity of the unknown customer's current behavior to the previous fraudulent behavior of a particular known fraudster.
[0055] As has been mentioned above, the concept of Immune Engineering is used in the above-described algorithm of fingerprinting in surroundings including at least one telecommunication network.
[0056] As has also been mentioned, the concept of Immune Engineering is applicable to more simple cases—just for cases of fraud detection in surroundings such as telecommunication networks, where characterizing data strings are pre-built using two or more abnormal situations in quite standard fraudulent behavior of subscribers with the provider, for example: entering a fraudulent subscription data and encountering further inconsistencies due to that.
[0057] Such data strings, though generally are also considered DNAs, will be called fraud DNAs. The component fraud genes are usually considered to represent fraud detectors as are and can be stored in so-called fraud detectors data bases.
[0058] The data strings of fraud DNAs may be shorter than the DNAs built for fingerprinting, and are standard not for a specific customer, but for the particular system where the suitable types of fraud are looked for.
[0059] Fraud detection can therefore be provided by comparison of real information incoming the network, with the fraud detectors stored in the detectors' database. To do that, the incoming information (say, taken from CDRs) is granulated into aggregated usage records, per customer, using a list of CDR fields (i.e., particular data fragments or sub-strings from CDR) which may match the fraud detectors. The aggregated usage records are built from the incoming information using the same processing rules, as those used for obtaining genes and building DNAs. The fraud is detected when there is found an aggregated usage records unit which comprises fragments matching to quite a lot (a sufficient percentage) of pre-selected fraud detectors.
[0060] Therefore, the fraud detection method comprises steps of:
[0061] storing said one or more fraud detectors in a fraud detectors' data base,
[0062] creating aggregated usage records of a number of respective customers, using newly incoming information stored in real time data bases, by selecting for said aggregated usage records data fragments from the real time data bases according to the processing rules applied for obtaining genes for building DNA;
[0063] comparing each of the aggregated usage records with contents of the fraud detectors' data base,
[0064] confirming the fraud detection whenever defining the aggregated usage records of at least one customer, comprising a number of data fragments matching said fraud detectors, wherein said number (of data fragments) exceeds a predetermined matching percent.
[0065] Both the fraud detection technique, and the fingerprinting technique require a preliminary stage of creating a data base (a set) of characterizing detectors, which can be called the stage of training the system on the behavior of interest.
[0066] The characterizing detectors' database can be created as follows:
[0067] obtaining a pre-built characterizing data string (DNA), for example by pre-processing initial information presenting a particular type of behavior (either normal or fraudulent) in a telecommunication network thereby creating the DNA being a binary succession comprising a combination of two or more fragments (genes), said combination of fragments being sufficient to make said DNA characterizing the particular type of behavior;
[0068] generating a plurality of different data sub-strings respectively suitable to said two or more fragments (genes) of the characterizing data string (DNA) by having respectively the same lengths;
[0069] matching each of the generated sub-strings with said string,
[0070] considering one or more specific generated sub-strings to be detectors if matching a particular fragment (gene) of the string (DNA) at least partially,
[0071] storing thus obtained detectors in the detector's database.
[0072] So, there are three conditions for selecting the generated detectors to be stored in the data base of detectors: they are to be of a predetermined length(s), there should be a minimal number of specific detectors which are sufficient for identification of the behavior of interest, the detectors are to be different and should match to genes of the DNA according to a selected matching principle (say, a partial matching principle of r-contiguous common bits).
[0073] According to the above principle, the following detectors' data bases can be created in a system:
[0074] detectors' data base for specific fraudulent behavior of a user X in the network;
[0075] detectors' data base for specific normal behavior of a user Y in the network.
[0076] detectors' data base for fraudulent behavior in the network;
[0077] detectors' data base for normal behavior in the network.
[0078] The detectors generation is preferably performed continuously, i.e., the detectors' data base can be updated from time to time.
[0079] According to the proposed technique, the detectors stored in the detectors' database preferably have a life span depending on their activity, i.e. the frequency of their use for comparing with the real data (the newly incoming information or aggregated usage records). Most active (coinciding) detectors are able to become constant members of the detectors' data base, while the minimally active ones may be replaced with new ones.
[0080] The invention will be described in more detail using the preferred embodiments illustrated below.
[0081]FIG. 1a illustrates a block-diagram of the training stage of the method and a part of the system performing the method, namely a subsystem for building a model of normal behavior.
[0082]FIG. 1b illustrates a block-diagram of the training stage of the method and a subsystem for modeling a fraudulent behavior, for further detecting such a behavior.
[0083]FIG. 2 illustrates a block-diagram showing how the trained system detects a specified type of behavior using the detectors' data base.
[0084]FIG. 3 illustrates a block-diagram of a fingerprinting method and a fraud detection method, based on the principle of Immune Engineering.
[0085]FIGS. 4a-4 d illustrate particular examples of usage records which may be used for building DNAs or aggregated usage records, fields of the records being related to genes composing DNAs.
[0086] Let us explain the block diagram of training, which is shown in FIG. 1a, on a particular example. As has been mentioned, FIG. 1a illustrates a concept of training the system (let it be called an Immune Engineering system) for further performing various operations, for example—for further use in the fingerprinting technique for recognizing the client. In our example, we will demonstrate the system training for a normal typical behavior of a particular client, and will use the fields (parameters) which form some usage records of telephone calls. Let the usage records will be voice usage records, fields of which are illustrated in a table shown in FIG. 4a.
[0087] The training is started by extracting information from a usage records database 10 which stores "historic" information on regular behavior of a number of clients. Information stored in 10 comprises various usage records. For example, there are records related to telephone sessions being voice conversations, faxes or data transmissions, initiated by a number of clients of a particular network. The data base 10 may comprise other usage records, such as IP flows usage records, Login usage records, Bandwidth usage records.
[0088] We will explain the block-diagram with the aid of Example 1:
[0089] In our example, we extract the voice usage records of a particular client identified by his (her) telephone number (say, # 1111111) from the data base 10, and forward them to pre-processing in block 12.
[0090] Let, in our example, the pre-processing is applied only to three fields out of six fields of the voice usage records shown in FIG. 4: field 1 (Terminating number), field 3 (Call type) and field 5 (Call duration). Say, for the purposes of our analysis field 2 is not used since it is identical to field 1 for the voice usage records, field 4 (start time of the call) is considered not important for the example, and additional services (field 6) used during the call—such as entering a credit card number by the keyboard—are not taken into account.
[0091] In this example, the pre-processing is performed for a predetermined characterizing period of time. The pre-processing of the terminating number constitutes coding of the (7 to 14)-digit number into a 4-digit number. Three possible types of call sessions (voice, fax and data) can be coded by 5 binary digits, and then re-coded by 2 digits. Say, the voice calls are indicated by "10", faxes by "15" and data calls by "25". The call duration is extracted from the call records in the form of a binary register which does not overcome any changes in the pre-processing block 12.
[0092] The pre-processed information belonging to three fields of the voice usage records is entered into a block 14 for building a DNA string of a regular behavior of the client of interest. Block 14 may form a number of DNA strings for a number of clients, DNA string(s) for a regular behavior in the system; such strings are marked "self". The DNA is built as follows:
[0093] let the client used the voice services 40 times during the predetermined period of time, and called to three terminating numbers respectively pre-processed as 1235(10 times), 2678(20 times) and 1000 (10 times).
[0094] let, from those calls, the client spoke by phone (code "10") 10 times, and sent data (code "25") 30 times.
[0095] let, a mathematically expected value D is taken for duration of the call sessions, and it can be written as a range: 5 seconds<D<1 hour 32 minutes.
[0096] Based on the above information, the characterizing string (DNA) of the client of interest can be built using separation marks (for example, ":")
1235(10) 2678(20) 1000(10): 10(10) 25(30): 5″-1h 32′, (1)
[0097] where
[0098] the first portion of the string up to the first separation mark reflects the used termination telephone numbers (sub-strings or genes) and the respective frequencies of calls to these numbers, the frequencies being put in brackets,
[0099] the middle portion up to the second separation mark reflects the used types of call sessions (other sub-strings or genes), and the respective frequencies (in brackets);
[0100] the last portion just shows the expectation of the call sessions' duration which was found characteristic for the client during the predetermined period.
[0101] Now, to learn characteristic elements (genes) of the DNA data string, a detector generator 16 starts generating random or pseudo-random detectors some of which may serve as data sub-strings of the DNA. In our example, there is no need in generating sub-strings of the type of call since there can be only three exact types known in advance and those three types can be taken as are to be detectors of the type of call. It is also useless to generate detectors of the call duration since the duration is already defined by the range in the DNA. In our example, the detector generator 16 generates detectors 10, 15 and 25 comparable to the type of call, and 4-digit sub-strings comparable to the coded Terminating numbers. To shorten the time to be spent for this process, the generator 16 may generate 4-digit combinations comprising r contiguous positions. Say, r=3 and the combinations list comprises such detectors as: 1230, 1231, . . . 2350, 2351 . . . 2670, . . . etc.
[0102] The generated detectors are sent to a matcher block 18 where they are compared to the genes of the DNA string. If a particular generated detector matches to a particular gene in the DNA string, this particular generated detector will be stored in a Detectors database 20. Actually, if the detectors are generated randomly, there will be such of them to be thrown away; however, if the detectors are generated pseudo-randomly, all of them will be stored in the database 20.
[0103] The database 20 may accumulate multiple sets of detectors, each set being formed for a particular client (subject).
[0104]FIG. 1b illustrates a block-diagram similar to that shown in FIG. 1a, but intended for training the system to a particular type of fraudulent behavior. All blocks of the block diagram are marked similarly to those in FIG. 1a, just by adding the digit 1 before their number. A data base 110 will comprise usage records concerning fraudulent activities of various kinds. Let's explain how the principle works, using Example 2.
[0105] In this example, the fingerprint engine receives all the historic URs (User Records) of a certain fraudster. The fraudster DNA is built based on the information coming from these URs (marked as 110). We will determine that fraudster as Fraudster.
[0106] Preprocessing of Incoming URs is performed in a pre-processor block 112. Assume that block 112 received all the URs 110 that were generated from Fraudster activities. Suppose that according to the Fraudster's URs:
[0107] Fraudster has used the company services 400 times, so 400 URs were received.
[0108] Fraudster called to the following terminating numbers respectively pre-processed as:
[0109] 1235 (100 times); 2033 (130 times); 2122 (90 times) 3434 (50 times); 2678 (20 times); 1000 (10 times)
[0110] Fraudster used the following services respectively pre-processed as:
[0111] 10 (300 times). Note: code '10' means 'speaking by phone'. 25 (100 times). Note: code '25' represents 'sending data'.
[0112] Fraudster called to the following area codes:
[0113] 03 (30 times); 02 (200 times); 001516 (170 times)
[0114] DNA Building is performed at block 114.
[0115] We will set weights, based on the above occurrences through a so-called Weight Function which can be defined as follows.
[0116] Prior Definitions:
[0117] n=Number of counters (for example, a number of used terminating numbers; a number of used services; a number of used area codes, etc)
[0118] ci=Counter of index i, i={overscore (1 . . . n)} (for example, counter of a particular terminating number—how much calls were made to this number)
[0119] wi=Weight value for ci, i={overscore (1 . . . n)} (for example, weight of calling to a particular terminating number)
[0120] The Weight Function Description:
[0121] Note: the following assumption always exists:
[0122] The importance of that assumption is that there is no affect of the weight mechanism on the overall counting (summary of all the counters). There is only different division of the overall counting (give to one, take from another . . . ). So, we can set the weight mechanism off, for certain fields, without harming the overall behavior.
[0123] Following are the calculated weight values:
[0124] Fraudster's called terminating numbers:
[0125] 1235 (100 times), weight=1.05; 2678 (20 times), weight=0.21 1000 (10 times), weight=0.11; 3434 (50 times), weight=0.52 2122 (90 times), weight=0.94; 2033 (130 times), weight=1.36
[0126] Used services:
[0127] 10 (300 times), weight=1.24; 25 (100 times), weight=0.4
[0128] Area codes:
[0129] 03 30 times), weight=0.17; 02 (200 times), weight=1.14 001516 (170 times), weight=0.97
[0130] Based on the above information, the characterizing string (DNA) of the client can be built from "genes" using separation marks (":"):
1235(1.05) 2678 (0.21) 1000(0.11) 3434(0.52) 2122(0.94) 2033(1.36): 10(1.24) 25(0.4): 03(0.17) 02(1.14) 001516(0.97) (2)
[0131] where:
[0132] The first portion of the string up to the first separation mark reflects "genes" formed from the used termination telephone numbers and the respective weights of calls to these numbers (the weights being put in brackets).
[0133] The middle portion up to the second separation mark reflects "genes" formed from the used types of call sessions and the respective weights (in brackets).
[0134] The last portion comprises "genes" reflecting the called area codes and the respective weights (in brackets).
[0135] Detectors Generation (block 116) in Example 2 is performed just from the whole genes values. There will be no manipulation (like sub-string or randomizing) on the genes' values.
[0136] In yet a further example, the usage records may comprise information reflected in tables shown in FIGS. 4A and 4B, concerning cases where one or more clients in the past performed a specific known type of fraudulent behavior in the system, for example with respect to a Login technique for further use of IP services.
[0137] However, other combinations of genes are possible, even such similar to those typical for the fingerprinting technique. Using such information, the system is able to build a data string called a fraud DNA to detect any attempt of using the system according to such a fraud again. Also in this case, there will be necessary to select detectors of such a fraud characteristic string. The technology of building a fraud DNA and selecting detectors for that, though being similar to the part of fingerprinting technique described in the Examples 1 and 2, slightly differs from that in obtaining the characterizing genes.
[0138] Suppose, we have received from an Expert several parameters, that, for his(her) opinion, characterize a type of fraud which is typical for the system. Let us also, for the example's sake, consider these parameters to be "Used services", "Area code" and "Called terminating telephone number". So, these three parameters in a combination undoubtedly describe the fraud.
[0139] 3.1 Parameter "used services", just for the example, will be any of the two codes of the used services:
[0140] "10": "25".
[0141] 3.2 Parameter "area code":
[0142] "03"; "02"; "001516".
[0143] 3.3 Parameter "called terminating number" can be any of the following codes of such numbers:
[0144] 1235, 2678, 1000, 3434, 2122, 2033. The Expert presents the coded numbers, which are further hashed (randomized) to obtain fraud parameters as follows:
[0145] "0235", "1235", "2235" . . . "9235"
[0146] "1230", "1231", "1232" . . . "1239"
[0147] "0678", "1678", "2678" . . . "9678"
[0148] "2670", "2671", "2672" . . . "2679"
[0149] "0000", "1000", "2000" . . . "9000"
[0150] 3.4. The fraud DNA can be built according to the above-proposed scenario, where the fraud genes are considered to be equal to the fraud parameters presented, without weight coefficients.
[0151] 3.5. Fraud detectors will be considered to be equal to the fraud genes, r respectively.
[0152]FIG. 2 illustrates a block diagram for detecting matching genes in the information reflecting incoming usage records. It can be used both for terminating the fingerprinting method, and for the fraud detection technology.
[0153] In FIG. 2, block 22 illustrates data bases of current incoming information or current usage records. Block 24 signifies pre-processing of the incoming usage records so that they might be compared (block 26) with detectors stored in the detectors' data bases 20 or 120. If, for a particular task of fingerprinting or fraud detection, a considerable number of the stored detectors match to a considerable number of fragments in the usage records, it is likely that the behavior of interest is allocated.
[0154]FIG. 3 illustrates a combined and more detailed block-diagram according to which the trained system (such that has accumulated characterizing detectors of a particular type of behavior or of a particular fraud) may detect whether a new incoming data, in the form of newly incoming usage records, matches the particular behavior (normal or fraudulent) to which the system was trained in advance. In other words, FIG. 3 is a combination of FIG. 1a (1 b) with FIG. 2 and is drawn for illustrating both the fingerprinting principle, and the principle of fraud detection. Block 11 indicates a general operation of obtaining genes for building DNA. It can be done by analytical pre-processing the historical usage records (blocks 10, 12 or 110, 112) as it is done in the fingerprinting technology, but can be done by direct selecting fraud genes for building fraud DNA in the technique of fraud detection. For each DNA (a plurality 1 . . . k of DNAs for various types of behavior may be built in the system), a set of detectors is created and such sets are respectively stored in the detectors' multiple data bases schematically marked 20, 120.
[0155] To compare the new incoming data of various clients 1 . . . m to the stored detectors, the respective incoming usage records 40 are pre-processed (block 42) into so-called incoming aggregated usage records (blocks 44). The aggregated usage records are built per client, during some period of time (which is not obligatory the same as that used for building DNA) and using the same pre-processing procedure (block 42 is equivalent to block 12). The aggregated usage records (44) are further compared to all specific collections of detectors which had been stored in the detectors data bases (20, 120) during the training process. Namely, a second matcher block (46) is responsible for comparing fields in a particular accumulated usage record 44 relating to a particular client (j) with at least one set of detectors of DNAh stored in the detectors data base 20. Actually, the aggregated usage record 44 of a particular client can be and is compared to all sets 1 . . . k of the detectors. If a considerable number of detectors of a specific set stored in the detectors' databases 20, 120 coincide with the respective fields of the aggregated records (second matcher 46), that user (j) for which the aggregated records have been built can be a candidate for matching the fingerprinting criteria with the client for which the set of detectors had previously been formed in the detectors database. If that specific set of detectors is a set of fraud detectors, the user (j) is found to perform the fraud known to the system. The decision concerning a particular client and each specific DNA is made at a decision block 50.
[0156] One version of the decision making will be described using the Example 1 from FIG. 1a:
[0157] Let, a period of time is set for searching. During this period, there comes a call from an unknown originating number (i.e., not having any bad or good history) and the usage record of the call is processed as follows:
[0158] 1238 (the 4-digits code of the terminating number), type is 10 (voice), duration is 10′: 1238, 10, 10′.
[0159] Suppose that we check the calls each hour, and each hour add new information to the aggregated record.
[0160] Let, the next hour two calls are added to the aggregated record:
[0161] 2381, 10, 20′, and 1238, 10, 2′.
[0162] Now, we may build the aggregated usage records (44) which will remind, by format, a newly built DNA string:
[0163] 1238(2), 2381(1): 10 (3): 10′ or 20′ or 2′
[0164] Or, by the originating numbers, the aggregated usage records are as follows:
[0165] 1238(2), 10, 10′ or 20′;
[0166] 2381, 10, 2′.
[0167] A number of the fields which coincide to the detectors stored in the detectors database will indicate the degree of closeness of the unknown client's behavior to the behavior to which the system was trained.
[0168] The results of comparison the aggregated records to detectors are accumulated in an accumulating block 48:
[0169] a) for the number 1238: 9(2), 1(2), 1, which means:
[0170] nine detectors in the data base 20 coincided to the terminating number, and the number was repeated twice;
[0171] one detector of the type of call coincided twice;
[0172] the call duration matches, and this fact is marked by "1";
[0173] b) for the number 2381 no detectors coincided to the termination number, and the call from the number 2381 is excluded from the analysis. Finally, to obtain the conclusion of the decision block 50 whether the fingerprinting found or not found, we may statistically estimate the representative results, and consider that ⅓-rd activity of the unknown number seems matching to the trained criteria (i.e., 66%). The decision threshold should be selected in advance, to convert the obtained probability into a decision.
[0174] Further, incoming records of other clients can be checked in a similar manner, and for each client there will be obtained an estimate as of the number of fields in the aggregated record which coincided with the detectors stored in the data base 20. At last, one or more clients will be found, that match the fingerprinting criteria according to a predetermined number of detectors in the detectors' data base coinciding to the fields of the clients' aggregated usage record.
[0175] Another version of processing the incoming usage records, matching and decision making will be described using Example 2 from FIG. 1b.
[0176] Pre-reprocessing of incoming URs will be performed as follows. Suppose that we received incoming URs that were generated in the previous 10 days. These URs will be aggregated according to the calling numbers. Let us suppose that these URs came from two different calling numbers. These calling numbers are respectively pre-processed as 1022 and 1033. The calling numbers represent two different clients, and two aggregated URs will be built for these two numbers.
[0177] There were 160 URs with calling number 1022 in which:
[0178] The following terminating numbers were called respectively pre-processed as:
[0179] 1235 (40 times); 2122 (20 times); 2033 (50 times);
[0180] 3333 (20 times); 8767 (10 times); 9191 (10 times);
[0181] 9001 (10 times);
[0182] The following services were used:
[0183] 10 (100 times); 25 (60 times)
[0184] The following area codes were called:
[0185] 02 (70 times); 001516 (40 times); 04 (20 times);
[0186] 06 (10 times); 08 (10 times); 09 (10 times)
[0187] There were 200 URs with calling number 1033 in which:
[0188] The following terminating numbers were called, and respectively pre-processed as:
[0189] 1000 (20 times); 3434 (10 times); 1212 (60 times);
[0190] 1984 (80 times); 2222 (20 times);
[0191] The following services were used:
[0192] 10 (50 times); 25 (150 times);
[0193] The following area codes were called:
[0194] 02 (50 times); 09 (80 times); 052 (40 times); 08 (30 times);
[0195] Matching of the Preprocessed URs Versus Different DNAs, Including the Fraudster DNA.
[0196] We will match every preprocessed (aggregated) UR versus the stored DNAs, including the Fraudster DNA, using the following algorithm:
[0197] For each preprocessed (aggregated) usage record from j={overscore (1 . . . m)}, where j—index of aggregated usage record, m—the number of new users to be studied, we will set all the gene-counters of all the pre-built DNAs to zero.
[0198] For each pre-built DNA from h={overscore (1 . . . k)}, where h—index of DNA's entry and k—number of pre-built DNA, and for each gene in the DNA i={overscore (1 . . . n)}, where i—index of gene in the DNA, n—number of genes in the DNA, the following comparison is provided with a field "i" in the aggregated UR: If the field's "i" value content (from aggregated usage record UR j) is included in (sufficiently close to) i from DNA h, and thus matches to detectors in the detectors data base, increase the gene-counter of gene i from DNA h by the number of appearances multiplied with the Weight parameter.
[0199] Based on the above method, we received the following results of matching.
[0200] 1. Matching Results of the Calling Number 1022 Preprocessed UR Versus the Fraudster DNA (2):
[0201] For terminating numbers genes, according to matching detectors:
[0202] 1235: 40*1.05; 2122: 20*0.95; 2033: 50*1.36
[0203] Matching result for terminating numbers:
[0204] (40*1.05)+(20*0.95)+(50*1.36)=129
[0205] For services genes, according to matching detectors:
[0206] 10: 100*1.24; 25: 60*0.4
[0207] Matching result for services:
[0208] (100*1.24)+(60*0.4)=148
[0209] For area codes genes, according to matching detectors_:
[0210] 02: 70*1.14; 001516: 40*0.97
[0211] Matching result for area codes:
[0212] (70*1.14)+(40*0.97)=118.6
[0213] 2. Matching Results of Calling Number 1033 Preprocessed UR Versus Fraudster DNA (2):
[0214] For terminating numbers' genes, according to_matching detectors:
[0215] 1000: 20*0.11; 3434: 10*0.52
[0216] Matching result for terminating numbers:
[0217] (20*0.11)+(10*0.52)=7.4
[0218] For services genes, according to matching detectors:
[0219] 10: 50*1.24; 25: 150*0.4
[0220] Matching result for service:
[0221] (50*1.24)+(150*0.4)=122
[0222] For area codes, according to matching detectors: 02: 50*1.14, and Matching result for area codes: (50*1.14)=57
[0223] To determine whether there is a Match (i.e., whether the Fraudster was detected), we will analyze the matching results from the preprocessed URs versus the Fraudster DNA.
[0224] We will set the threshold of suitable matching percent to 0.7. Then, we will define a so-called Matching Percent Function (MP):
[0225] Prior Definitions:
[0226] n=Number of genes in DNA and fields in UR
[0227] m=Number of usage records UR corresponding to m users to be studied
[0228] ci=Matching counter of gene i, i={overscore (1 . . . n)}. Number of matching between the aggregate UR field i values and the best-matched DNA's gene i. Each match is multiplied with the relevant weight parameter.
[0229] The Matching Percent (MP) Function's Description:
[0230] Based on the above, we will calculate the matching percent MP of every preprocessed UR versus the Fraudster DNA, using the Matching Percent Function:
[0231] The MP of the calling number 1022 is suitable (higher then the threshold), so the person that is calling from number 1022 is suspected, by the fingerprint engine, as the Fraudster.
[0232] The above examples illustrate that, using the Immune Engineering approach, a fingerprint engine can be trained to a known fraudster, and thereby can become able to detect the known fraudulent behavior when the fraudster renews the activity under a different identity.
[0233] The same data and procedure, as has been just described in Example 2, can be applied for illustrating how the fraud detection is performed in the Example 3. Suppose, we build the fraud DNA using the same data and procedure. In such a case, the matching percent for number 1022 (0.82), exceeding the threshold of 0.8, will mean that behavior of the client having the calling number 1022 corresponds to the known fraud type in the system. The example similar to the fingerprinting technique is taken for the sake of simplicity, but other parameters (genes) can form the fraud DNA.
[0234]FIGS. 4a-4 d illustrate, in the form of tables, various kinds of usage records which can be used in a network for fingerprinting and/or fraud detection. In practice, in new generation networks which combine various services, more than one kind of usage records can be analyzed to build a characterizing combined DNA of a particular client or fraudster. Each of the tables comprises a list of fields (parameters) of the usage record, which is usually stored in the usage record data base for this specific type of service. The tables also point out the type of each field that is usually coded by a number, and describe how the value of the parameter will be indicated in the field.
[0235] For example, for modern cellular networks, a client's complex activity may be recorded by: bandwidth usage records (FIG. 4c), Voice usage records (FIG. 4a) and, if the cellular network enables transmitting data to IP networks, the client's activity records may be completed using IP flows usage records (FIG. 4d) and Login usage records (FIG. 4b). Therefore, DNA of such a client using the cellular network may be built using all kinds of the usage records shown in FIGS. 4a-4 d. The resulting DNA will be a combination of genes corresponding to several of the mentioned fields.
[0236] Though the invention has been described with reference to particular non-limiting examples, it should be appreciated that other versions of the method can be proposed and should be considered part of the invention that is defined by the claims, which follow.
|Cited Patent
|Filing date
|Publication date
|May 4, 1936
|Mar 28, 1939
|American Box Board Co
|Title not available
|Title not available
|Title not available
|Title not available
|Citing Patent
|Filing date
|Publication date
|Oct 3, 2007
|May 10, 2011
|Symantec Corporation
|Detecting an audio/visual threat
|Sep 28, 2005
|Aug 16, 2011
|J&L Group International, Llc
|Programmable load forming system, components thereof, and methods of use
|Jun 30, 2006
|Sep 4, 2012
|Sophos Plc
|Method and system for classification of software using characteristics and combinations of such characteristics
|Mar 30, 2009
|Jan 29, 2013
|Sophos Plc
|Method and system for classification of software using characteristics and combinations of such characteristics
|Mar 12, 2013
|Sprint Communications Company L.P.
|Telecom fraud detection using social pattern
|May 7, 2010
|Apr 2, 2013
|Sprint Communications Company L.P.
|Communications-service fraud detection using special social connection
|Apr 18, 2011
|Sep 24, 2013
|Retail Decisions, Inc.
|Automatic rule discovery from large-scale datasets to detect payment card fraud using classifiers
|Mar 30, 2010
|Mar 18, 2014
|Verizon Patent And Licensing Inc.
|Speech usage and performance tool
|Mar 8, 2013
|Mar 25, 2014
|Sprint Communications Company L.P.
|Telecom fraud detection using social pattern
|Apr 30, 2009
|Dec 23, 2014
|Telefonaktiebolaget L M Ericsson (Publ)
|Deviating behaviour of a user terminal
|Jun 21, 2006
|Jan 13, 2015
|Genband Us Llc
|Method and apparatus for identifying and monitoring VoIP media plane security keys for service provider lawful intercept use
|Nov 22, 2006
|Jun 2, 2015
|At&T Intellectual Property I, L.P.
|Methods and apparatus for automatic security checking in systems that monitor for improper network usage
|Apr 1, 2005
|Oct 6, 2005
|Ectel Ltd.
|Detection of outliers in communication networks
|Jun 30, 2006
|Jan 3, 2008
|Ben Godwood
|Method and system for classification of software using characteristics and combinations of such characteristics
|Mar 30, 2010
|Oct 6, 2011
|Verizon Patent And Licensing Inc.
|Speech usage and performance tool
|Apr 30, 2009
|Mar 8, 2012
|Telefonaktiebolaget L.M Ericsson (Publ)
|Deviating Behaviour of a User Terminal
|Apr 21, 2011
|Oct 27, 2011
|Retail Decisions
|Automatic rule discovery from large-scale datasets to detect payment card fraud using classifiers
|U.S. Classification
|713/188, 726/6, 726/26
|International Classification
|Cooperative Classification
|European Classification
|Oct 8, 2002
Owner name: ECTEL LTD., ISRAEL
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:GOLOBRODSKY, OLEG;RONEN, DAVID;REEL/FRAME:013371/0268
Effective date: 20021001
|Mar 25, 2011
Owner name: CVIDYA 2010 LTD., ISRAEL
Free format text: CHANGE OF NAME;ASSIGNOR:ECTEL LTD.;REEL/FRAME:026026/0561
Effective date: 20100505
|Apr 28, 2014
|Fee payment
Year of fee payment: 4


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Electronic Beats Magazine Issue 3/2012
While the plural of anecdote might not be data, our current collection of monologues and stories certainly makes for good reading. In fact, our Fall issue not only functions like an anecdotal bricolage, but also centers on the cut-up thematically. From the technique's explosion in the visual arts in the beginning of the twentieth century to its vital role in the context of sampling and electronic music, assembling parts from different sources to create a new whole is about more than just making art—it's a way of seeing the world's narrative tapestry. Best wishes, Max Dax, Editor-in-Chief
ELECTRONIC BEATS CONVERSATIONS ON ESSENTIAL ISSUES N° 31 · FALL 2012 CHRIS LOWE / PET SHOP BOYS: "Doing things differently." CAN COOLY G H.P. BAXXTER THE KILLS


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The new iPhone is tipped to pack 'in-cell' touch technology, which reduces the need for extra sensors and glass.
Looking for phones? CNET editors' reviews of the best phones include product photos, video, and user reviews.
If you're looking for something beyond simple photo retouching and filtering for your late-model phone, Photoshop Touch hits the mark, but look at user reviews before you leap.
Apple's entry-level phone offers something unique. But is it too old?
Bill Detwiler cracks open the iPhone 6S and discovers plenty of hardware upgrades, but no major changes to the internal layout.
Made of leather, titanium and solid sapphire, and with its own concierge service included, the Vertu New Signature Touch is a seriously luxurious Android phone. Andy Hoyle went hands-on.
We see which phone takes better shots in low-light -- the iPhone 6S Plus, the Samsung Galaxy S6 or the older iPhone 6.
The Chinese smartphone maker confirms it is making a Windows 10 phone that will debut before year's end.
At $99, the Alcatel One Touch Evolve is an affordable Android phone, but its dismal performance makes it not even worth that price.
For as little as $69 on Kickstarter, you can capture virtual-reality photos and videos using just your phone.
CEO John Chen runs into a little trouble taking us on a tour of BlackBerry's Priv Android phone. Is that a bad omen?


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Ear Surgery Q&A
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My son had his operation on Friday to have his ears pinned back. He has had some minor bleeding from his ears and a headache is this normal? READ MORE
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Freeport, Illinois Pet Friendly Hotels & Lodging
United States » Illinois » Freeport
Looking for a hotel in Freeport, IL that you can bring your pet to? We made sure that each one of the hotels below are pet friendly, so you can enjoy your trip with your pet by your side! Once you have found a pet friendly hotel, you can book your stay instantly from our website or call 866-212-1803 to speak with a pet travel agent.
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1060 Riverside Dr - Freeport, IL (Map)
Baymont Inn & Suites Freeport is pet friendly. Guests are welcome to bring 3 pets no more than 25 pounds of pet. The pet fee is $35.00 per stay.
Overview | Pet Policy | Map
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1551 Sleezer Home Rd - Freeport, IL (Map)
Super 8 Freeport allows pets to accompany their people at their pet friendly accommodation. The pet fee is $15 per pet, per day.
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text: Place Commonwealth Community Christian Preschool Today. Last updated: October 6, 2015 at 12:01 am Latest Stories in Entertainment MOVIES: 31 days of Halloween Get into the Halloween spirit by watching one of these scary movies. in National General Mills recalls 1.8 million boxes of Cheerios The company is recalling the original and honey nut flavored varieties.


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Porterville, Calif. Scheduled to Consider Rescinding LGBT Pride Month
July 16, 2013 by Maureen McCarty, HRC Deputy Director of Marketing
This evening, California's Porterville City Council is scheduled to consider whether to rescind a proclamation designating June as LGBT Pride Month and to change the process by which city proclamations are approved.
Mayor Virginia Gurrola issued the proclamation on June 4 at a contentious city council meeting. Issuing proclamations is solely the jurisdiction of the mayor, but the rest of the city council typically signs the document. However, none of the city councilors joined with the mayor in supporting the proclamation.
Tonight's agenda includes both measures under the council's scheduled matters.
The Porterville City Council was the only city government in the state to support Proposition 8, the discriminatory ballot initiative that outlawed same-sex marriage in California in 2008. Last month, the U.S. Supreme Court returned marriage equality to California.
Top Posts
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June 1, 2015
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June 5, 2015
Watch: HRC Answers Your SCOTUS Questions
June 19, 2015


text:
Retailers plan to hire an increased number of temporary workers this holiday season, according to a survey by the global consulting firm Hay Group.
Visitors to Walmart this fall have the opportunity to learn about Straight Talk Wirelsss and support the Make-A-Wish foundation in the process.
And the award for most effective use of social media in the pet category goes to…
The National Retail Federation is set to go to court in order to block the proposed $7.25 billion settlement of a federal antitrust lawsuit over Visa and MasterCard credit card swipe fees.
Greek yogurt maker Fage has partnered with Bobby Flay, chef, restaurateur and cookbook author, to help everyday chefs create extraordinary meals using the simplest of ingredients: plain Greek yogurt.
Brown Shoe Company has acquired the Sam & Libby brand and reunited it with its founders, Sam and Libby Edelman.
Fashion and technology combine to surprise customers and engage them in new ways at Bloomingdale's flagship in New York City and other locations across the country.
Bed Bath & Beyond is offering a trio of Granite Gold branded products as part of an exclusive new Home Care Collection.
The future North American grocery business of Kraft Foods will deliver steady and profitable top-line growth, consistent bottom-line growth and a superior dividend payout, according to the business' future executive team.


text:
Advances in Inorganic Chemistry
Inorganic Reaction Mechanisms
Edited by
- Colin Hubbard, Institute for Inorganic Chemistry, University of Erlangen-Nürnberg, Egerlandstr 1, 91058 Erlangen, Germany
- Rudi van Eldik, University of Erlangen-Nurnberg, Germany
The Advances in Inorganic Chemistry series presents timely and informative summaries of the current progress in a variety of subject areas within inorganic chemistry ranging from bio-inorganic to solid state studies. This acclaimed serial features reviews written by experts in the area and is an indispensable reference to advanced researchers. Each volume of Advances in Inorganic Chemistry contains an index, and each chapter is fully referenced. This, the 54th volume in the series continues this tradition providing comprehensive reviews by leading experts in the field with the focus on inorganic and bioinorganic reaction mechanisms.View full description
For organic and inorganic chemists. Also for physical chemists and biochemists.
Book information
- Published: July 2003
- Imprint: ACADEMIC PRESS
"These...volumes continue the tradition of representing timely summaries of the current state of understanding on a wide variety of 'special topics'..." -JOURNAL OF THE AMERICAN CHEMICAL SOCIETY


text:
Jamie Blanchard is a truly funny comedian with a very likable personality on stage. He is a fast rising comic on the Minneapolis scene. He has a clever story telling style with distinctive rants that's sure to keep you wanting more.
Get to know Jamie as he brings you through his life experiences Citing Family, Friends, relationships and anything else that's bugging him. It'll be funny for you and Therapy for him.
So sit back and enjoy the comedy of Jamie Blanchard. You'll laugh because it's funny, but you'll clap because it's true.
Jamie Blanchard talks about the predicament between texting vs. calling.
Jamie Blanchard talks about his reliance on bathroom technology.
Jamie Blanchard talks about how having married friends can suck.
Jamie Blanchard talks about hitting on a married woman.
Jamie Blanchard makes his own soundtrack at the gym.
Jamie Blanchard on asking for permission as a married man.


text:
We're all well aware that you've gotta look out for Mother Nature these days, and if you're not, just go outside and ask yourself if it feels right. Looking after the environment is important, and every little bit helps--that's why G-Star Raw came up with their Raw for the Oceans (RTFO) collection.
Exclusive First Look: G-Star Raw's RTFO x Pharrell
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text:
BLACKSBURG, Va. — When Frank Beamer addressed the media on Monday, he brushed past any talk of Virginia Tech's return to the top 25 and ignored the still-warm memories of the team's 27-17 win against North Carolina just two days earlier.
Nope, he was in a Pittsburgh state of mind, and for good reason.
The Panthers visit Lane Stadium this week as owners of a four-game winning streak against the Hokies. That includes last season's 35-17 shellacking at Pittsburgh that knocked the Hokies out of the top 25 and kept them out until this week.
"This is a team that we've had a hard time beating," Beamer said. "They've gotten us the last four times. And going back and checking, Alabama hasn't done that, LSU hasn't done that, Texas A&M hasn't done that, Clemson hasn't done that …"
Beamer added Florida State and Miami to that list, erroneously, but his point was made. In recent times, dating back to 2000, no team has held such sway over the Hokies.
"But Pittsburgh has," Beamer continued. "Last time we played them — 537 yards against us, [we] turned the ball over four times, only had 59 yards rushing. Just a team we've had a hard time beating, whether it's matchups or whatever, it's a team we haven't had great success against."
Junior receiver Willie Byrn said the coaching staff's distaste for the Pittsburgh streak has been apparent this week. Meanwhile, he and his fellow players — who were in elementary school during Virginia Tech's first three losses — remain fixated on last year's debacle.
"You can certainly sense a little bit of … just a revenge factor," Byrn said. "I don't know about all four games, but certainly last year. All of our players were there last year so we just want to go out there and beat them and give them a little taste of what they gave us last year."
That fire definitely burns for senior linebacker Tariq Edwards, who said he was appalled when he watched film of last year's defeat.
"Watching that game, it's kind of disgusting just to watch it," he said.
Both Beamer and senior quarterback Logan Thomas said Pittsburgh's physicality was something that stood out last year.
"Offense and defense, they brought it," Thomas said.
"I think they are very, very tough," Beamer said. "I think offensively, just like Alabama, they are tough, aggressive, hard-nosed and run right at you."
And in the tradition of big, physical, play-making recievers such as Larry Fitzgerald who terrorized the Hokies at the start of the four-game streak, this year's Panthers boast a pair to be watched in senior Devin Street (6-4, 195) and freshman Tyler Boyd (6-2, 185).
The duo has combined to average 217.5 receiving yards per game and make Pittsburgh just one of three teams nationally to have two players averaging more than 100 yards per game.
"Street is a tall guy and Boyd, a young guy, but he's explosive," Beamer said. "They've got about 44 catches between them. That, and they've got a big ol' offensive line, all over 6-6 except the center, and defensively they fly around and are aggressive. A good football team."
Like Virginia Tech, the Panthers' lone loss came to a top-five team in the first week of the season (a 41-13 setback against Florida State). Since then, Pittsburgh has shown it can win a shootout (58-55 at Duke) and prevail in a low-scoring affair (14-3 against Virginia).
All of it adds up to what Beamer thinks will be Virginia Tech's most important game to date.
"Both lost to a top-five football team and they've done very well since, so we're on very similar paths in that regard," Beamer said. "Big ballgame, conference game … it's going to be a good game."


text:
What's the deal with these Knockout Attacks? Three More ŌĆ£KnockoutŌĆØ Attacks Reported In Philadelphia Area
PHILADELPHIA (CBS) ŌĆö ŌĆ£KnockoutŌĆØ attacks have been reported in several states around the country and now investigators believe three people have been attacked in our area.
Police in Lower Merion are investigating two attacks in the area, and Philadelphia detectives are investigating an attack in Northeast Philadelphia.
ItŌĆÖs a violent crime that in other parts of the country has proven fatal.
Videos from cities around the country show people being punched and beaten at random.
The attackers are calling their crimes a game, the goal being to knock out the victim with one punch.
Mark Cumberland is a victim of a ŌĆ£KnockoutŌĆØ assault.
ŌĆ£Someone asked me for a cigarette and by the time I got my hands out my pocket I was getting hit by four kids.ŌĆØ
He says, ŌĆ£It was hard seeing and IŌĆÖm still having trouble breathing and swallowing.ŌĆØ
Cumberland was walking out of a Fox Chase pizza shop on November 11th when he was attacked.
ŌĆ£ThereŌĆÖs no reason at all. I mean, I didnŌĆÖt get robbed, they didnŌĆÖt take nothing from me. They just beat me up.ŌĆØ
Lt. Frank Higgins of the Lower Merion Police says, ŌĆ£He punched him right in the mouth and knocked him to the ground. The victim began to scream and yell for someone to call the police.ŌĆØ
A neighbor of the victim, Jeri Greenfield says, ŌĆ£I think itŌĆÖs absolutely horrible. I think this is a beautiful neighborhood and I didnŌĆÖt expect anything like that here.ŌĆØ
An elderly man was also attacked when he was mowing his lawn outside of his home.
The suspect in that attack is still on the loose.
Bruce Myer, a neighbor of the elderly victim says, ŌĆ£A kid came up to him and just punching him in the mouth. He ended up laying the street with his lawnmower.ŌĆØ
The only apparent motive in these attacks, as in all ŌĆ£KnockoutŌĆØ attacks, is to inflict injury on a random victim.
Myer says, ŌĆ£The kid did it on a dare. He said give me five dollars and IŌĆÖll knock that guy out.ŌĆØ
ItŌĆÖs very sad that before you used to walk on the street with no worries whatsoever,ŌĆØ neighbor Al Ciavijo said.
The elderly victim is now using a cane and a walker to get around. He has had to undergo multiple medical procedures.
That suspect is still on the loose, as are the suspects in the Northeast Philadelphia attack.
Quoting NWP:
Wasn't this posted last week?
I don't know. I log on for a few days, then I don't make it back on for a few days. I'm not on here Every. Single. Day.
It's disturbing.
Quoting NWP:
Wasn't this posted last week?


text:
Jersey Skylands Labrador Retriever Club, Inc
Welcome to the Jersey Skylands Labrador Retriever Club, Inc. Welcome Page. We have included a lot of information about our club,members and activities. Our membership is open to all who wish to promote the interests of the breed and like to participate in a wide range of activities with their Labradors.
Jersey Skylands Labrador Retriever Club, Inc. was founded as a non-profit organization in 1992 and serves the northwestern New Jersey, eastern Pennsylvania and southern New York Region.
All members have agreed to support or participate in club sponsored activities and to abide by the club's Code of Ethics. Members are welcome from within and outside the United States.
The club provides a Puppies and Adult Dogs Available service to help match quality labrador puppies and older dogs with loving, responsible homes.
JSLRC is an AKC licensed club, an area club of the Labrador Retriever Club, Inc. (the AKC parent club of the Labrador Retriever in the United States) and a member of the New Jersey Federation of Dog Clubs.
We sponsor Back to Back Speciality Shows with the Newton Kennel Club, fun field training, specialty match shows, educational meetings and booths, health clinincs and many other fun activities.
Anyone interested in membership or club activities, please stop by our Membership/Member Services page and/or our Meetings/Events page for more information.
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Jersey Skylands Labrador Retriever Club has partnered with Paw Print Genetics to provide high quality, affordable testing for your dogs. To order, go to https://www.pawprintgenetics.com/ or call them at: 1-509-483-5950. The following discounts are available now and valid through 9/30/15. Using discount code JSLRC, save 20% off any order or 30% off any Labrador Retriever panel: https://www.pawprintgenetics.com/products/breeds/76/
JSLRC, Inc. is a member club of the:
American Kennel Club
Labrador Retriever Club
NJ Federation of Dog Clubs


text:
I have owned for more than 15 years. I haven't lost a nickel because I didn't sell. Lots and lots of dividends though-more than 10 % per year. Know the rule of 76?
I have owned NLY for many years. No different from my other stocks. They go up and down! If you want to gamble go to Las Vegas. If you want a nice dividend, buy and hold NLY.
Sentiment: Strong Buy
Has MGM ever considered becoming profitable. The stock price hasn't moved in years. And buying Wynn?


text:
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Make Your "Five-Oh" Go Faster and Smoother
Learn how to pump up the volume in your pony.
It's a long way from Detroit to Milan, but Hudson's attempt to bridge that gap was nothing less than amazing.
V-8 power makes this the best C1 ever.
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Giving a 1927 Chrysler a really personal touch...and 3,000 rivets.
Dodge's assembly plant on Monroe Street was a testament to the highs and lows of the American automobile industry.
Putting a unique grille on your hot rod, rat rod, or custom is easier than you think.
Ford was just ramping up production of their new 1942 models when World War II rerouted production for a greater cause.
A peek inside "Flatjack" Jack Meyer's amazing flathead Ford collection.
Mustang's third body style emerges.
Giving credit to the man who many consider the reason for the Corvette's long lasting success.
We've picked 11 classics, built between 1965 and 1998 that we feel offer a great blend of style, individuality, performance and some cases,...
Upgrading a 1966 Mustang's Baer system from two-piston PBR caliper to six-piston Baer caliper.
After a light refresh Roger Moore's "other" spy car is ready to take to the screen again.
After four decades of slumber one of Zagato's finest creations returns to the limelight.
We pick what we think are the five best Lamborghinis ever.
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If not for the Corvette Sebring Racer, the life of the Corvette may have been a brief one.
Watch as the experts from Steele Rubber Products show you how to replace these often forgotten but very important window seals.
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From hauling cargo to hauling style.
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The first cars roll into place for this exceptional exhibit of automotive design.
Flashy paint, billet, chrome and lots of polish make these street rods stand out.
A 2000 Cobra R takes an unplanned adventure at Hallett Motor Racing Circuit.
When it was all done over $24 million dollars had crossed the auction blocks.
These candy colored haulers have been retired from workhorse duty.
These show stoppers are the heart and soul of the event!
Putting the new Focus ST through the gauntlet.
Ford Hits The Jackpot In Vegas
The most common question I hear about my cars is "how much"?
Things are moving fast at the site of the south's newest raceway.
Having a godfather is one thing, I had a "rodfather".
Just. Wow. Yeah, that pretty much sums it up.
We buy them, work on them, spend money on them, treat them better than we do ourselves, so why don't we drive our classic cars more often?
Brutally effective in their design, these retired racers also hold a certain beauty.
The big show was anything but routine this year.
AutoTrader Classics Editor Brian Medford travels to Streetside Classics in Powder Springs, GA to talk about one of his favorite cars, the Impala SS.
Steel may be real, but fiberglass has class!
Taking a walk around the pits at Tulsa Raceway Park.
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Your face is the first thing people notice about you and the first thing they'll describe to the police after you open all their mail. Make a lasting impression with this Groupon.
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