基于ARIMA-SWGARCH模型的DDoS攻击准确可靠检测

K. V. Raghavender, P. Premchand
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引用次数: 2

摘要

DDoS攻击检测是发现网络上发生的攻击,导致持续丢包或丢包的过程。由于网络流量轨迹和模式的变化,准确检测DDoS是最复杂的任务。在我们之前的工作中,我们引入了带宽洪水攻击检测方法来解决这个问题。但是,该方法在不同的流量模式和路径下表现不佳。本研究通过引入混合ARIMA-SWGARCH模型来解决这一问题,该模型的主要目标是通过分析不同的测量网络流量来检测DDoS攻击。在这里,度量网络模式的初始规范化是通过使用Box-Cox变换完成的。然后进行白色检验,找出交通模式时间序列的异方差特征。然后应用ARIMA-SWAGARCH混合模型对网络中发生的DDoS攻击进行有效检测。在MATLAB仿真环境中对该方法进行了总体评估,证明了所提出的研究方法能够保证对网络中发生的DDoS攻击进行最优可靠的检测。
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Accurate and reliable detection of DDoS attacks based on ARIMA-SWGARCH model
DDoS attack detection is the process of finding the attacks happening on a network that causes continues packet drops or losses. Accurate detection of DDoS is the most complex task due to varying network traffic traces and patterns. This is resolved in our previous work by introducing the method namely bandwidth flooding attack detection method. However, this method failed to perform better with varying traffic patterns and traces. This is resolved in this research work by introducing the method namely hybrid ARIMA-SWGARCH model whose main goal is to detection DDoS attacks by analysing the varying measured network traffic. Here initially normalisation of measure network patterns is done by using the Box-Cox transformation. And then the white test is performed to finding the heteroscedasticity characteristics of time series of traffic patterns. And then the hybrid ARIMA-SWAGARCH model is applied to efficiently detect the DDoS attacks happening on the network. The overall evaluation of this method is conducted in the MATLAB simulation environment from which it is proved that the proposed research method can ensure the optimal and reliable detection of DDoS attacks happening on the network.
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