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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

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.

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1010.2511v5.pdf - Updated Version
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SATE10_13_Marfcat_Mokhov.pdf - Presentation

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 > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Concordia University > Gina Cody School 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
  • Modular Audito Recognition Framework (MARF)
  • Static Code Analysis
  • Faculty of Engineering and Computer Science
Identification Number:NIST Special Publication (SP) 500-283
Keywords:static code analysis, vulnerability fingerprinting, machine learning, data mining, MARF, MARFCAT
ID Code:36058
Deposited By: Serguei Mokhov
Deposited On:05 Jan 2012 17:03
Last Modified:18 Jan 2018 17:36
Related URLs:
Additional Information:Editors: Vadim Okun, Aurelien Delaitre, Paul E. Black


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