Interest Flooding Attack detection method base-on reconstruction-based Completely Random Forest in NDN
Interest Flooding Attacks are considered to be one of the biggest threats to Named Data Networks.Existing IFA detection methods are mainly based on the PIT expiration rate,interest packet satisfaction rate or the name distribution of interest packets,and the currently proposed methods are vulnerable to the problem of traffic fluctuations and cannot distinguish attacks from traffic fluctuations quickly and accurately.To address this problem,a RecForest based IFA detection method is proposed,which collects the information of interest packets within the PIT for reconstruction and restricts the forwarding of malicious interest packets to mitigate the impact of IFA.Simulation results show that the method can reduce the problem of false positives caused by traffic fluctuations and effectively detect IFA.
Named Data NetworkingInterest Flooding Attackattack detection method
万方数据
维普
