{'fraction_non_alphanumeric': 0.0088339222614841, 'fraction_numerical': 0.0, 'mean_word_length': 6.269230769230769, '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}}
Novel steganography detection using an artificial immune system approach

Research in steganalysis is motivated by the concern that communications associated with illicit activity could be hidden in seemingly innocent electronic transactions. By developing defensive tools before steganographic communication grows, computer security professionals may be better prepared for the threat. This research investigated an artificial immune system approach to novel steganography detection for digital images. The results show promising detection and false positive rates.