Method and system for detecting malicious behavioral patterns in a computer, using machine learning


Ontology type: sgo:Patent     


Patent Info

DATE

2013-08-20T00:00

AUTHORS

Robert Moskovitch , Dima Stopel , Zvi Boger , Yuval Shahar , Yuval Elovici

ABSTRACT

Method for detecting malicious behavioral patterns which are related to malicious software such as a computer worm in computerized systems that include data exchange channels with other systems over a data network. According to the proposed method, hardware and/or software parameters that can characterize known behavioral patterns in the computerized system are determined. Known malicious code samples are learned by a machine learning process, such as decision trees, Naïve Bayes, Bayesian Networks, and artificial neural networks, and the results of the machine learning process are analyzed in respect to these behavioral patterns. Then, known and unknown malicious code samples are identified according to the results of the machine learning process. More... »

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