Abstract
As of today, Distributed Denial of Service Attacks remain one the most devastating threats online. This paper presents an estimation model that integrates the discrete wavelet transform (DWT) and Chi-Square test (\( X_{2} \)) for detecting DDoS attacks. The present model presents a distributed architecture reducing the risk of single point of failure and increasing the reliability of the system. First, we uses the DWT to decompose the traffic data. Then, the obtained detail (high-frequency) components is used as input variable to forecast future traffic attack. To ensure a complete distribution of our system we test the PAXOS protocol which give a reliable communication between detection systems. The model is tested using real datasets of DDoS traces. So, our proposed system outperforms other conventional models that use a centralized architecture.
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Ouerfelli, F.E., Barbaria, K., Zouari, B., Fachkha, C. (2020). Distributed Detection System Using Wavelet Decomposition and Chi-Square Test. In: Kallel, S., Cuppens, F., Cuppens-Boulahia, N., Hadj Kacem, A. (eds) Risks and Security of Internet and Systems. CRiSIS 2019. Lecture Notes in Computer Science(), vol 12026. Springer, Cham. https://doi.org/10.1007/978-3-030-41568-6_24
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DOI: https://doi.org/10.1007/978-3-030-41568-6_24
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