Abstract

Interest flooding attacks (IFAs) seriously harm named data networking by overwhelming the pending interest table of a content router. In this letter, we propose a Gini impurity-based IFA detection mechanism that can effectively detect IFAs, and a malicious Interest recognition mechanism that can distinguish the malicious Interests with legitimate ones. In addition, we evaluate the performance of our mechanism. The simulation results validate that the mechanism can accurately detect and effectively mitigate IFAs.

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