Network coding achieves optimal throughput in multicast networks. However, throughput optimality relies on the network nodes or routers to code correctly. A Byzantine node may introduce junk packets in the network (thus polluting downstream packets and causing the sinks to receive the wrong data) or may choose coding coecients
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. Intra-session network coding is known to be vulnerable to Byzantine attacks: malicious nodes can inject bogus packets, which get combined with legitimate blocks at downstream nodes, thus preventing decoding of original packets and degrading the overall performance. In this paper, we provide a novel approach that can identify the precise location of all Byzantine attackers in systems with intra-session network coding. A key ingredient of our approach is a novel homomorphic MAC scheme for expanding subspaces (SpaceMac) that allows to eliminate any uncertainty in identifying attackers via subspace properties. To the best of our knowledge, our scheme is the first that can identify precisely all Byzantine attackers, and at the same time has both low computation (sub- millisecond) and communication overhead (20 bytes per data block). Simulation results show that, even when there are multiple colluding attackers in a network, all of them can be successfully identified in a very short time.