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Distributed Detection System Using Wavelet Decomposition and Chi-Square Test

机译:小波分解和卡方检验的分布式检测系统

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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.
机译:到目前为止,分布式拒绝服务攻击仍然是在线上最具破坏性的威胁之一。本文提出了一种估计模型,该模型结合了离散小波变换(DWT)和卡方检验(X_2)来检测DDoS攻击。本模型提出了一种分布式架构,该架构降低了单点故障的风险并提高了系统的可靠性。首先,我们使用DWT分解交通数据。然后,将获得的详细信息(高频)分量用作输入变量,以预测未来的流量攻击。为了确保我们系统的完整分发,我们测试了PAXOS协议,该协议在检测系统之间提供了可靠的通信。该模型使用DDoS跟踪的真实数据集进行了测试。因此,我们提出的系统优于使用集中式体系结构的其他常规模型。

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