Distributed denial of service attack detection using an ensemble of neural classifier
Computer Communications
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In contrast to traditional brute-force attacks, RoQ (Reduction of Quality) attacks are periodic, stealthy, yet potent, which exploit the vulnerability of adaptation mechanisms to undermine certain services. As the application-level peer-to-peer (p2p) protocols depend on a recovery-adjustment process to maintain global consistency of routing information when peers join and leave the systems, we propose a novel breed of RoQ attacks in structured p2p systems: (1) We induce a general model for RoQ attacks, and then derive in structured p2p networks a new attack form that RoQ attackers periodically create concurrent failure through manipulation of massive nodes, degrading the system performance repeatedly. (2) We explore the impacts of RoQ attacks on Chord with detailed analysis and theoretical estimations, and confirm them by simulation results on p2psim, including successful lookup ratio and lookup latency. Moreover, we also discuss the detection and defense against such attacks and the improvements of protocols for attack tolerance.