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FRRED: Fourier robust RED algorithm to detect and mitigate LDoS attacks

机译:FRRED:傅里叶鲁棒红算法检测和缓解LDOS攻击

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As most of consumer electronics are connected to the Internet, network attacks can cause massive damage and loss of data to the users. By sending periodic packet bursts to bottleneck routers, Low-Rate Denial-of-Service (LDoS) attacks can degrade the throughput of TCP applications while being hard to be detected. In this paper, we introduce Power Spectrum Density Entropy (PSD-entropy) to detect LDoS attacks. We also propose a Fourier transform based Robust RED (FRRED) queuing algorithm to preserve TCP throughput when faced with LDoS attacks. This novel Active Queue Management (AQM) Algorithm firstly detects the suspicious attack packets based on their arrival time and then filter the attack packets based on Power Spectrum Density (PSD) entropy. We perform extensive simulations in NS-3 to evaluate the performance of FRRED. Compared to other AQM algorithms, FRRED has the lowest False Positive Rate and can preserve nearly the full TCP throughput.
机译:由于大多数消费电子产品连接到互联网,网络攻击可能会对用户造成大规模损坏和数据丢失。通过将周期性数据包发送到瓶颈路由器,低速拒绝服务(LDOS)攻击可能会降低TCP应用程序的吞吐量,同时难以检测到。在本文中,我们引入了功率谱密度熵(PSD熵)来检测LDOS攻击。我们还提出了一种傅里叶变换基于鲁棒的红色(FRRED)排队算法,以在面对LDOS攻击时保留TCP吞吐量。这种新的活动队列管理(AQM)算法首先根据其到达时间检测可疑攻击数据包,然后基于功率谱密度(PSD)熵过滤攻击分组。我们在NS-3中进行广泛的模拟,以评估FRRED的性能。与其他AQM算法相比,FRRED具有最低的误率,可以保护几乎完整的TCP吞吐量。

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