Using API Sequence and Bayes Algorithm to Detect Suspicious Behavior
Authors:
- Cheng WangCWCheng Wang
- Jianmin PangJPJianmin Pang
- Rongcai ZhaoRZRongcai Zhao
- Xiaoxian LiuXLXiaoxian Liu
- 1 January 2009
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 544-548
Abstract
Computer viruses have become the main threat of the safety and security of industry. Unfortunately, no mature products of anti-virus can protect computers effectively. This paper presents an approach of virus detection which is based on analysis and distilling of representative behavior characteristic and systemic description of the suspicious behaviors indicated by the sequences of APIs which called under Windows. Based on decompilation analysis, according to the determinant of Bayes algorithm, and by the validation of abundant sample space, the technique implements the virus detection by suspicious behavior identification.Keywords
This publication has 2 references indexed in Scilit:
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- Data mining methods for detection of new malicious executables2002