Análise e contra-ataque à poluição e whitewashing em sistemas P2P de vídeo ao vivo

Abstract

Live streaming video applications on the Internet are becoming more popular in the last years. The ease of publishing and accessing content through such applications has at tracted great attention from users and researchers. The P2P architecture has obtained a prominent place in this context, mainly because it is more fault tolerant and overcome the scalability issues present in the client-server model. However, due to its distributed characteristics, the P2P networks can be more susceptible to attacks and malicious be havior. In this work, we analyze the impact of pollution attacks and whitewashing in P2P live streaming systems. To combat these attacks, simple mechanisms and decentralized reputation are proposed and implemented by a prototype application running on a real network environment, set in PlanetLab. Our results show that pollution attacks are harmful to P2P live streaming systems. When 10% of peers are malicious, the remaining peers in the system receive more than 90% of data polluted. Furthermore, the average overhead in network bandwidth reaches 230% at peak times, forcing the peers to use three times the bandwidth required in a system without pollution attacks. The proposed reputation mechanism, tested on PlanetLab testbed, quickly blocks isolated pollution attacks, reducing the amount of polluted data received to 6% and the overhead to 5%. In the case of pollution attack combined with whitewashing, the proposed reputation mechanism reduces the overhead in the system from 112% to 20% and the amount of polluted data from 70% to 19%.