Hamm-grams are a new class of fixed-length regular expressions over bytes with single-character wildcards, mined efficiently with LSH and clustering to yield more robust features than n-grams for malware classification and detection.
BitShred: Feature Hashing Malware for Scalable Triage and Semantic Analysis.Security2011, pp
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TrapNet applies PCA-based FloatHash vectors and graph community detection to enable unsupervised malware fingerprinting and family attribution from static analysis.
citing papers explorer
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Hamm-Grams: An Algorithm for Mining Regular Expressions of Bytes
Hamm-grams are a new class of fixed-length regular expressions over bytes with single-character wildcards, mined efficiently with LSH and clustering to yield more robust features than n-grams for malware classification and detection.
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Applying Graph Analysis for Unsupervised Fast Malware Fingerprinting
TrapNet applies PCA-based FloatHash vectors and graph community detection to enable unsupervised malware fingerprinting and family attribution from static analysis.