Mokhov, Serguei A. (2011) The use of machine learning with signal- and NLP processing of source code to fingerprint, detect, and classify vulnerabilities and weaknesses with MARFCAT. Technical Report. NIST, Gaithersburg, MD.
PDF (E-print of the technical report section.)
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PDF (Presentation slides for SATE2010 workshop.)
Official URL: http://samate.nist.gov/docs/NIST_Special_Publicati...
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.
|Divisions:||Concordia University > Faculty of Engineering and Computer Science > Computer Science and Software Engineering|
Concordia University > Faculty of Engineering and Computer Science > Concordia Institute for Information Systems Engineering
Concordia University > Research Units > Centre for Pattern Recognition and Machine Intelligence
Concordia University > Research Units > Computer Security Laboratory
|Item Type:||Monograph (Technical Report)|
|Authors:||Mokhov, Serguei A.|
|Series Name:||NIST SP|
|Date:||27 October 2011|
|Keywords:||static code analysis, vulnerability fingerprinting, machine learning, data mining, MARF, MARFCAT|
|Deposited By:||Serguei Mokhov|
|Deposited On:||05 Jan 2012 17:03|
|Last Modified:||05 Jan 2012 17:03|
|Additional Information:||Editors: Vadim Okun, Aurelien Delaitre, Paul E. Black|
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