Using API Sequence and Bayes Algorithm to Detect Suspicious Behavior

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.