Deguang Kong, Donghai Tian, Qiha Pan, Peng Liu and Dinghao Wu Semantic aware attribution analysis of remote exploits Security and Communication Networks 6
We present SA3, a novel exploit code attribution analysis that combines semantics-based analysis and statistical modeling to automatically categorize given exploit code. SA3 extracts semantic features from exploit code through data anomaly analysis and then attributes the exploit to an appropriate class on the basis of our statistical model derived from a Markov model. The attribution analysis accuracy can be over 90% in different parameter settings with false positive rate of no more than 4.5%.
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