【摘 要】
：
Aim to improve the detection accuracy,anovel peer-to-peerbotnet detection method based on permutation entropy and adaptive information fusion algorithm was proposed.Permutation entropy was utilized to
【机 构】
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Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 13003
【出 处】
：
第十二届中国可信计算与信息安全学术会议
论文部分内容阅读
Aim to improve the detection accuracy,anovel peer-to-peerbotnet detection method based on permutation entropy and adaptive information fusion algorithm was proposed.Permutation entropy was utilized to characterize the complexity measure of networktraffic,which did not vary with the structure of peer-to-peer network,peer-to-peer protocol and attacktype.Kalman filter was utilized to detect the abnormalities of the complexity measure.Furthermore,the features of TCP packets were utilized to reduce the negative impact of web applications on botnet detection,especially the web applications that were based on peer-to-peer protocols.To get more accurate information fusion result,an adaptive information fusion algorithm was proposed tofuse the above detection results to get the final detection result,which combined Dempster-Shafer theory and Dezert-Smarandache the-ory by using their superiorities and overcoming their disadvantages.The experimentresultsshow that the proposed method is able to detect peer-to-peer botnet with higher accuracyand stronger robustness.
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