We propose a distributed approach to detect distributed denial of service attacks by monitoring the increase of new IP addresses. Unlike previous proposals for bandwidth attack detection schemes which are based on monitoring the traffic volume, our scheme is very effective for highly distributed denial of service attacks. Our scheme exploits an inherent feature of DDoS attacks, which makes it hard for the attacker to counter this detection scheme by changing their attack signature. Our scheme uses a sequential nonparametric change point detection method to improve the detection accuracy without requiring a detailed model of normal and attack traffic. In a multi-agent scenario, we show that by sharing the distributed beliefs, we can improve the detection efficiency. © 2003 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Peng, T., Leckie, C., & Ramamohanarao, K. (2003). Detecting distributed denial of service attacks by sharing distributed beliefs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2727 LNCS, pp. 214–225). https://doi.org/10.1007/3-540-45067-X_19
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