Identifying Malicious Nodes in Network-Coding- Based Peer-to-Peer Streaming Networks

Researchers show that network coding can greatly improve the quality of service in P2P live streaming systems (e.g., IPTV). However, network coding is vulnerable to pollution attacks where malicious nodes inject into the network bogus data blocks that will be combined with other legitimate blocks at downstream nodes, leading to incapability of decoding the original blocks and degradation of network performance. In this paper, we propose a novel approach to limiting pollution attacks by identifying malicious nodes. In our scheme, the malicious nodes can be rapidly identified and isolated, so that the system can quickly recover from pollution attacks. Our scheme can fully satisfy the requirements of live streaming systems, and achieves much higher efficiency than previous schemes. Each node in our scheme only needs to perform several hash computations for an incoming block, incurring very small computational latency in the range of several microseconds. The space overhead added to each block is only 20 bytes. The verification information given to each node is independent of the streaming content and thus does not need to be redistributed. The simulation results based on real PPLive channel overlays show that the process of identifying malicious nodes only takes a few seconds even in the presence of a large number of malicious nodes.