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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Automatic Generation of String Signatures for Malware Detection
verfasst von : Kent Griffin, Scott Schneider, Xin Hu, Tzi-cker Chiueh
Erschienen in: Recent Advances in Intrusion Detection
Verlag: Springer Berlin Heidelberg
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Scanning files for signatures is a proven technology, but exponential growth in unique malware programs has caused an explosion in signature database sizes. One solution to this problem is to use
string signatures
, each of which is a contiguous byte sequence that potentially can match many variants of a malware family. However, it is not clear how to automatically generate these string signatures with a sufficiently low false positive rate. Hancock is the first string signature generation system that takes on this challenge on a large scale.
To minimize the false positive rate, Hancock features a scalable model that estimates the occurrence probability of arbitrary byte sequences in goodware programs, a set of library code identification techniques, and diversity-based heuristics that ensure the contexts in which a signature is embedded in containing malware files are similar to one another. With these techniques combined, Hancock is able to automatically generate string signatures with a false positive rate below 0.1%.