Yabin Xu1, 2, 3, *, Ting Xu3, Xiaowei Xu4
CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1075-1089, 2020, DOI:10.32604/cmc.2020.09849
Abstract To improve the attack detection capability of content centric network (CCN),
we propose a detection method of interest flooding attack (IFA) making use of the feature
of self-similarity of traffic and the information entropy of content name of interest packet.
On 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 attacks. On 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, is.… More >
Login
Register
