Feedback-Based Content Poisoning Mitigation in Named Data Networking

Abstract

NDN has been widely recognized as a promising architecture for future network where universal in-network caches provide convenient for content distribution. However, the ubiquitous caches mount a significant problem, called content poisoning, in NDN. Most current mitigation schemes aim to mitigate the bogus Data packets in the cache store rather than prohibit evil producers and locate the valid content, or they inhibit both the legitimate sources and evil ones meanwhile during traceback. In this paper, we present a lightweight approach to mitigate content poisoning by clearing bogus Data packets in cache store and help network to adjust forwarding paths to retrieve legitimate Data packets. The proposed scheme can block the evil producer and protect the legitimate producer at the same time. Furthermore, it can detect and resist the content poisoning generated by the intermediate compromised routers too. We implement our scheme by comparing it with Immediate Failover in ndnSIM simulator. Simulation results show that our scheme can alleviate the content poisoning attacks quickly and effectively.