P2P-based botnets: structural analysis, monitoring, and mitigation

Botnets, which are networks of compromised machines that are controlled by one or a group of attackers, have emerged as one of the most serious security threats on the Internet. With an army of bots at the scale of tens of thousands of hosts or even as large as 1.5 million PCs, the computational power of botnets can be leveraged to launch large-scale DDoS (Distributed Denial of Service) attacks, sending spamming emails, stealing identities and financial information, etc. As detection and mitigation techniques against botnets have been stepped up in recent years, attackers are also constantly improving their strategies to operate these botnets. The first generation of botnets typically employ IRC (Internet Relay Chat) channels as their command and control (C&C) centers. Though simple and easy to deploy, the centralized C&C mechanism of such botnets has made them prone to being detected and disabled. Against this backdrop, peer-to-peer (P2P) based botnets have emerged as a new generation of botnets which can conceal their C&C communication. Recently, P2P networks have emerged as a covert communication platform for malicious programs known as bots. As popular distributed systems, they allow bots to communicate easily while protecting the botmaster from being discovered. Existing work on P2P-based hotnets mainly focuses on measurement of botnet sizes. In this work, through simulation, we study extensively the structure of P2P networks running Kademlia, one of a few widely used P2P protocols in practice. Our simulation testbed incorporates the actual code of a real Kademlia client software to achieve great realism, and distributed event-driven simulation techniques to achieve high scalability. Using this testbed, we analyze the scaling, reachability, clustering, and centrality properties of P2P-based botnets from a graph-theoretical perspective. We further demonstrate experimentally and theoretically that monitoring bot activities in a P2P network is difficult, suggesting that the P2P mechanism indeed helps botnets hide their communication effectively. Finally, we evaluate the effectiveness of some potential mitigation techniques, such as content poisoning, Sybil-based and Eclipse-based mitigation. Conclusions drawn from this work shed light on the structure of P2P botnets, how to monitor bot activities in P2P networks, and how to mitigate botnet operations effectively