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Low-rate Denial of Service (LDoS) attack is one of great threats to computing platform and big data center. LDoS attacks are difficult to be found because its average attack rate is low enough to evade traditional DoS-based countermeasures. In this paper, the propagation back (BP) model of neural network is used to establish the nonlinear model of network traffic, and a method of LDoS attacks detection...
Low-rate denial of service (LDoS) attacks send periodic pulse sequences with relative low rate to form aggregation flows at the victim end. LDoS attack flows have the characteristics of low average rate and great concealment. It is hard to detect LDoS attack flows from normal traffic due to low rate property. Network traffic measurement shows that aggregate network traffic is multifractal. In order...
It is widely recognized that distributed denial of service (DDoS) attacks can disrupt Web service and cause large revenue losses. However, effective defenses continue to be mostly unavailable. We design a novel DDoS security mechanism, which is a three-layer defense mechanism based on Web servers. Combining the characteristic of the traffic of Web servers and aiming at TCP/IP reference model, it utilizes...
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