Toward a source detection of botclouds: A PCA-based approach

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Abstract

Cloud computing security is often focused on data and users security and protection against external intrusions. However, it exists an area of cloud security that is often overlooked and that can have disastrous consequences: the conversion of cloud computing into an attack vector. Beyond a legitimate usage, the numerous advantages of cloud computing are exploited by attackers. Botnets supporting Distributed Denial of Service (DDoS) attacks are among the greatest beneficiaries of this malicious use. In this paper, we propose a novel source-based detection approach that aims at detecting the abnormal virtual machines behavior. The originality of our approach resides in (1) relying only on the system's metrics of virtual machines and (2) considering a source-based detection. Our approach is based on Principal Component Analysis to detect anomalies that can be signs of botcloud's behavior supporting DDoS flooding attacks. We also present the results of the evaluation of our detection algorithm. © 2014 International Federation for Information Processing.

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APA

Badis, H., Doyen, G., & Khatoun, R. (2014). Toward a source detection of botclouds: A PCA-based approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8508 LNCS, pp. 105–117). Springer Verlag. https://doi.org/10.1007/978-3-662-43862-6_13

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