The Content Pollution in Peer-to-Peer Live Streaming Systems: Analysis and Implications

Abstract

There has been significant progress in the development and deployment of peer-to-peer (P2P) live video streaming systems. However, there has been little study on the security aspect in such systems. Our prior experiences in Anysee exhibit that existing systems are largely vulnerable to intermediate attacks, in which the content pollution is a common attack that can significantly reduce the content availability, and consequently impair the playback quality. This paper carries out a formal analysis of content pollution and discusses its implications in P2P live video streaming systems. Specifically, we establish a probabilistic model to capture the progress of content pollution. We verify the model using a real implementation based on Anysee system; we evaluate the content pollution effect through extensive simulations. We demonstrate that (1) the number of polluted peers can grow exponentially, similar to random scanning worms. This is vital that with 1% polluters, the overall system can be compromised within minutes; (2) the effective bandwidth utilization can be sharply decreased due to the transmission of polluted packets; (3) Augmenting the number of polluters does not imply a faster progress of content pollution, in which the most influential factors are the peer degree and access bandwidth. We further examine several techniques and demonstrate that a hash-based signature scheme can be effective against the content pollution, in particular when being used during the initial phase.