The use of machine learning with signal- and NLP processing of source code to fingerprint, detect, and classify vulnerabilities and weaknesses with MARFCAT

Details The use of machine learning with signal- and NLP processing of source code to fingerprint, detect, and classify vulnerabilities and weaknesses with MARFCAT The use of machine learning with signal- and NLP processing of source code to fingerprint, detect, and classify vulnerabilities and weaknesses with MARFCAT

2010-10-12

arxiv.org/abs/1010.2511v6

Computer Science

Cryptography and Security

33 pages, 11 tables; some results presented at SATE2010; NIST, October 2011; shorter version of v5 appears in the NIST technic

Scientific paper

We present a machine learning approach to static code analysis and
fingerprinting for weaknesses related to security, software engineering, and
others using the open-source MARF framework and the MARFCAT application based
on it for the NIST's SATE2010 static analysis tool exposition workshop found at
http://samate.nist.gov/SATE2010Workshop.html

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