No abstract

No abstract

No abstract

No abstract

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.Keywords: malware analysis; algorithm classification; big data; feature extraction; machine learning; binary instrumentation; dynamic instruction flow.Reference to this paper should be made as follows: Zhao, J., Chen, S., Cao, M. and Cui, B. (2017)