{'fraction_non_alphanumeric': 0.03067484662576687, 'fraction_numerical': 0.014899211218229623, 'mean_word_length': 5.274725274725275, '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}}
Hash Algorithms: From Message Digests to Signatures

There are many information-sharing applications that are in use on modern networks today. Concurrently, there are a growing number of users sharing data of increasing value to both sender and recipient. As the value of data increases among users of information-sharing systems, the risks of unauthorized data modification, user identity theft, fraud, unauthorized access to data, data corruption, and a host of other business-related problems mainly dealing with data integrity and user authentication, are introduced. The issues of integrity and authentication play an important part in the economic systems of human society. Few would do business with companies and organizations that do not prove trustworthy or competent. For example, the sentence “I owe Alice US$500” has a hash result of “gCWXVcL3fPV8VrJNajm8JKAZZ,” while the sentence “I owe Alice US$5000” has a hash of “DSAyXRTza2bHLH46IPMrSqZZ.” As can be seen, there is a big difference in hash results between the two sentences. If an attacker were trying to misappropriate the $4500 difference, hashing would allow detection.