首页> 外文会议>Proceedings of the 2012 20th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems >Improving the Performance Efficiency of an IDS by Exploiting Temporal Locality in Network Traffic
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Improving the Performance Efficiency of an IDS by Exploiting Temporal Locality in Network Traffic

机译:通过利用网络流量中的时间局部性来提高IDS的性能效率

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Network traffic has traditionally exhibited temporal locality in the header field of packets. Such locality is intuitive and is a consequence of the semantics of network protocols. However, in contrast, the locality in the packet payload has not been studied in significant detail. In this work we study temporal locality in the packet payload. Temporal locality can also be viewed as redundancy, and we observe significant redundancy in the packet payload. We investigate mechanisms to exploit it in a networking application. We choose Intrusion Detection Systems (IDS) as a case study. An IDS like the popular Snort operates by scanning packet payload for known attack strings. It first builds a Finite State Machine (FSM) from a database of attack strings, and traverses this FSM using bytes from the packet payload. So temporal locality in network traffic provides us an opportunity to accelerate this FSM traversal. Our mechanism dynamically identifies redundant bytes in the packet and skips their redundant FSM traversal. We further parallelize our mechanism by performing the redundancy identification concurrently with stages of Snort packet processing. IDS are commonly deployed in commodity processors, and we evaluate our mechanism on an Intel Core i3. Our performance study indicates that the length of the redundant chunk is a key factor in performance. We also observe important performance benefits in deploying our redundancy-aware mechanism in the Snort IDS[32].
机译:传统上,网络流量在数据包的标头字段中表现出时间局部性。这种局部性是直观的,并且是网络协议语义的结果。然而,相比之下,尚未对分组有效载荷中的局部性进行详细研究。在这项工作中,我们研究了分组有效载荷中的时间局部性。时间局部性也可以看作是冗余,并且我们观察到分组有效载荷中的显着冗余。我们研究了在网络应用程序中利用它的机制。我们选择入侵检测系统(IDS)作为案例研究。像流行的Snort一样的IDS通过扫描数据包有效载荷来查找已知的攻击字符串。它首先从攻击字符串数据库构建有限状态机(FSM),然后使用数据包有效负载中的字节遍历此FSM。因此,网络流量中的时间局部性为我们提供了加速这种FSM遍历的机会。我们的机制可动态识别数据包中的冗余字节,并跳过其冗余FSM遍历。我们通过与Snort数据包处理阶段同时执行冗余识别来进一步并行化我们的机制。 IDS通常部署在商品处理器中,我们在Intel Core i3上评估我们的机制。我们的性能研究表明,冗余块的长度是性能的关键因素。我们还发现在Snort IDS中部署我们的冗余感知机制具有重要的性能优势[32]。

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