Classification of DDoS Attacks and Flash Events using Source IP Entropy and Traffic Cluster Entropy

Srinath Sureshkumar
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Abstract

Distributed Denial of Services (DDoS) attack is one of the most dangerous exploits capable of affecting an organization’s reputation and functioning. Today several tools are available to launch one with ease. It is extremely difficult to differentiate these attacks from flash events. Flash Crowds are events where plenty of legitimate requests for a common web resource come into the server. When the incoming traffic into a server exceeds the peak limit the possibility of a server crashing or hanging also increases. Due to the congestion caused by the huge amount of illegitimate traffic in DDoS attacks, the server is unable to complete the legitimate service requests and the server’s resources are overloaded with these illegitimate requests. We propose an Entropy based classification technique which differentiates legitimate flash crowds and illegitimate DDoS attack traffic.
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基于源IP熵和流量簇熵的DDoS攻击和Flash事件分类
分布式拒绝服务(DDoS)攻击是最危险的攻击之一,能够影响组织的声誉和功能。现在有几个工具可以轻松地启动一个。将这些攻击与闪电事件区分开来是极其困难的。Flash crowd是指大量对公共web资源的合法请求进入服务器的事件。当进入服务器的流量超过峰值限制时,服务器崩溃或挂起的可能性也会增加。由于DDoS攻击中大量的非法流量造成拥塞,导致服务器无法完成合法的业务请求,导致服务器资源过载。我们提出了一种基于熵的分类技术来区分合法的闪电人群和非法的DDoS攻击流量。
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