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

机译:使用机器学习检测计算机中恶意行为模式的改进方法和系统

摘要

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. Accordingly, hardware and/or software parameters are determined in the computerized system that is can characterize known behavioral patterns thereof. Known malicious code samples are learned by a machine learning process, such as decision trees and artificial neural networks, and the results of the machine learning process are analyzed in respect to the behavioral patterns of the computerized system. Then known and unknown malicious code samples are identified according to the results of the machine learning process.
机译:用于检测与恶意软件有关的恶意行为模式的方法,该恶意软件行为包括计算机化系统中的计算机蠕虫,该计算机化系统包括通过数据网络与其他系统的数据交换通道。因此,在计算机系统中确定可以表征其已知行为模式的硬件和/或软件参数。已知的恶意代码样本是通过机器学习过程(例如决策树和人工神经网络)学习的,并且针对计算机系统的行为模式分析了机器学习过程的结果。然后根据机器学习过程的结果识别已知和未知的恶意代码样本。

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