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A memory-based NFA regular expression match engine for signature-based intrusion detection

机译:基于内存的NFA正则表达式匹配引擎,用于基于签名的入侵检测

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Signature-based intrusion detection is required to inspect network traffic at wire-speed. Matching packet payloads against patterns specified with regular expression is a computation intensive task. Hence, the design of hardware accelerator to speed up regular expression matching has been an active research area. A systematic approach to detect regular expression is based on finite automaton. The space-time tradeoff between deterministic finite automaton (DFA) and non-deterministic finite automaton (NFA) is well-known. DFA can offer constant throughput but it may suffer from the state explosion problem. Hence, implementation of DFA for large pattern sets on embedded device with limited on-chip memory may not be viable. NFA requires linear space but the throughput can be very low. Implementations of NFA with hardwired circuits can overcome the speed deficiency by exploiting the massive parallelism offered by dedicated hardware circuitries, but this approach does not support efficient dynamic updates. In this paper, we shall present a memory-based architecture for the implementation of NFA to speed up regular expression matching for signature-based intrusion detection. The proposed method supports dynamic updates and offers constant throughput so that it can be used to supplement the existing DFA-based methods in handling large pattern sets.
机译:需要基于签名的入侵检测以线速检查网络流量。将分组有效载荷与用正则表达式指定的模式进行匹配是一项计算量大的任务。因此,用于加速正则表达式匹配的硬件加速器的设计一直是活跃的研究领域。一种检测正则表达式的系统方法是基于有限自动机的。确定性有限自动机(DFA)和非确定性有限自动机(NFA)之间的时空折衷是众所周知的。 DFA可以提供恒定的吞吐量,但可能会遭受状态爆炸问题的困扰。因此,对于具有有限片上存储器的嵌入式设备上的大型模式集实施DFA可能不可行。 NFA需要线性空间,但吞吐量可能非常低。使用硬连线电路的NFA实施可以通过利用专用硬件电路提供的大规模并行性来克服速度缺陷,但是这种方法不支持有效的动态更新。在本文中,我们将提出一个基于内存的体系结构以实现NFA,以加快基于签名的入侵检测的正则表达式匹配。所提出的方法支持动态更新并提供恒定的吞吐量,因此可用于在处理大型模式集时补充现有的基于DFA的方法。

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