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首页> 外文期刊>IEEE communications letters >Information theory based detection against network behavior mimicking DDoS attacks
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Information theory based detection against network behavior mimicking DDoS attacks

机译:基于信息论的针对模仿DDoS攻击的网络行为的检测

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DDoS is a spy-on-spy game between attackers and detectors. Attackers are mimicking network traffic patterns to disable the detection algorithms which are based on these features. It is an open problem of discriminating the mimicking DDoS attacks from massive legitimate network accessing. We observed that the zombies use controlled function(s) to pump attack packages to the victim, therefore, the attack flows to the victim are always share some properties, e.g. packages distribution behaviors, which are not possessed by legitimate flows in a short time period. Based on this observation, once there appear suspicious flows to a server, we start to calculate the distance of the package distribution behavior among the suspicious flows. If the distance is less than a given threshold, then it is a DDoS attack, otherwise, it is a legitimate accessing. Our analysis and the preliminary experiments indicate that the proposed method- can discriminate mimicking flooding attacks from legitimate accessing efficiently and effectively.
机译:DDoS是攻击者和检测者之间的间谍游戏。攻击者正在模仿网络流量模式以禁用基于这些功能的检测算法。区分模仿DDoS攻击与大规模合法网络访问是一个开放的问题。我们观察到僵尸使用受控功能将攻击包泵送到受害者,因此,流向受害者的攻击总是共享某些属性,例如打包分发行为,这是短期内合法流不具备的。基于此观察,一旦出现可疑流到服务器,我们就开始计算可疑流之间的包裹分发行为的距离。如果距离小于给定的阈值,则表示是DDoS攻击,否则,则是合法访问。我们的分析和初步实验表明,提出的方法可以有效地将模仿洪泛攻击与合法访问区分开。

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