Malware algorithm classification method based on big data analysis Online publication date: Mon, 06-Feb-2017
by Jingling Zhao; Shilei Chen; Mengchen Cao; Baojiang Cui
International Journal of Web and Grid Services (IJWGS), Vol. 13, No. 1, 2017
Abstract: Internet technology has greatly increased the number of malware attacks on networks. Consequently, it has also elevated the importance of automatic malware detection and classification technology based on big data analysis in the field of information security. This paper presents a new method for classifying malware algorithms that exhibits both high accuracy and high coverage. The method combines big data analysis with software security technologies such as feature extraction, machine learning, binary instrumentation and dynamic instruction flow analysis to achieve automated classification of malware algorithms. 20 classification experiments prove the correctness of the method. We also discuss future directions for improving the method.
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