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On the Difficulty of Scalably Detecting Network Attacks

机译:难以扩张地检测网络攻击

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Most network intrusion tools (e.g., Bro) use per-flow state to reassemble TCP connections and fragments in order to detect network attacks (e.g., SYN Flooding or Connection Hijacking) and preliminary reconnaissance (e.g., Port Scans). On the other hand, if network intrusion detection is to be implemented at high speeds at network vantage points, some form of aggregation is necessary. While many security analysts believe that such per-flow state is required for many of these problems, there is no clear proof that this is the case. In fact, a number of problems (such as detecting large traffic footprints or counting identifiers) have scalable solutions. In this paper, we initiate the study of identifying when and how a security attack detection problem can have a scalable solution. We use tools from Communication Complexity to prove that the common formulations of many well-known intrusion detection problems (detecting SYN Flooding, Port Scans, Connection Hijacking, and content matching across fragments) require per-flow state. Our theory exposes assumptions that need to be changed to provide scalable solutions to these problems; we conclude with some systems techniques to circumvent these lower bounds.
机译:大多数网络入侵工具(例如,BRO)使用每流状态来重新组装TCP连接和片段,以检测网络攻击(例如,SYN洪水或连接劫持)和初步侦察(例如,端口扫描)。另一方面,如果要在网络Vantage点的高速实现网络入侵检测,则需要某种形式的聚合。虽然许多安全分析师认为许多这些问题需要这种每流动状态,但没有明确证明这是这种情况。实际上,许多问题(例如检测大的流量足迹或计数标识符)具有可扩展的解决方案。在本文中,我们启动了识别安全攻击检测问题何时以及如何具有可扩展解决方案的研究。我们使用来自通信复杂性的工具来证明许多知名入侵检测问题的常见配方(检测SYN泛洪,端口扫描,连接劫持和跨片段的内容匹配)需要每流状态。我们的理论暴露了需要更改的假设,以为这些问题提供可扩展的解决方案;我们与一些系统技术结束,以规避这些下限。

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