Analysis of malicious flows via SIS epidemic model in CCN

Content Centric Networking (CCN) is a novel network architecture that attempts to overcome the limitations of today's network. Security is supported fundamentally by CCN. In this paper, the spreading of malicious flows is modelled via a modified N-intertwined epidemic model. We consider three types of malicious flows: Interest flooding attack flow, content poisoning flow, and rumor. To the best of our knowledge, this paper is a first attempt to apply epidemic model to flow analysis in CCN. We introduce a forwarding matrix to the original epidemic model, which can characterize the forwarding strategy chosen by nodes. Based on modified epidemic model, we derive the upper bound for the number of nodes that affected by malicious flows, and conclude that forwarding strategy can affect the spreading of malicious flows. Matlab-based study and packet-level simulation are performed to verify our model, and the results show that spreading of malicious flows is related to forwarding strategy, and our epidemic model can better characterize malicious flows than original model.