{'fraction_non_alphanumeric': 0.012195121951219513, 'fraction_numerical': 0.0, 'mean_word_length': 5.389221556886228, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An empirical study of botnets on university networks using low-interaction honeypots

Malware and Botnets in particular have risen to be premier threats to computing assets. As computer criminals continue to improve their attack methods it is essential that the security community have tools at their disposal to quickly identify and remediate these ever increasing attacks. Honeypots are increasingly becoming a tool of the trade as security administrators enhance their security and follow a security in depth model for combating security threats. In this thesis, we use interaction honeypots to study the attack behaviors of mobile devices on a "real-world" university wireless network. This research project will address this security issue by investigating effective solutions to identify compromised machines in a university network. The experimental results will presented based on using low interaction honeypots such as Honeyd in a live testing environment. In addition, various honeypots are tested and compared and our analysis will be documented as well.