To improve the attack detection capability of content centric network(CCN),we propose a detectionmethod of interest flooding attack(IFA)making use of the feature of self-similarity of traffic and the information entr...
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To improve the attack detection capability of content centric network(CCN),we propose a detectionmethod of interest flooding attack(IFA)making use of the feature of self-similarity of traffic and the information entropy of content name of interest *** the one hand,taking advantage of the characteristics of self-similarity is very sensitive to traffic changes,calculating the Hurst index of the traffic,to identify initial IFA *** the other hand,according to the randomness of user requests,calculating the information entropy of content name of the interest packets,to detect the severity of the IFA attack,***,based on the above two aspects,we use the bilateral detection method based on non-parametric CUSUM algorithm to judge the possible attack behavior in *** experimental results show that flooding attack detectionmethod proposed for CCN can not only detect the attack behavior at the early stage of attack in CCN,but also is more accurate and effective than other methods.
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