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Implementation of reduced storage finite automata in field-programmable gate arrays.

机译:在现场可编程门阵列中实现减少存储的有限自动机。

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Deep Packet Inspection (DPI) has been widely adopted in detecting network threats such as intrusion, viruses and spam. It is challenging, however, to achieve high speed DPI due to expanding rule sets and ever-increasing line rates. One key issue is that the size of the finite automata falls beyond the capacity of on-chip memory, thus incurring expensive off-chip memory accesses. This thesis presents a hardware-based DPI engine that utilizes novel techniques to minimize the storage requirements for finite automata. We propose a technique that uses a modified form of content addressable memory, interleaved memory banks, and data packing. The performance evaluation results show that up to 2.5 Gbps throughput can be reached using a single engine in a contemporary FPGA chip. In many cases, the single engine approach can yield over 90% reduction in the memory usage over a straightforward approach.
机译:深度数据包检测(DPI)已被广泛用于检测入侵,病毒和垃圾邮件等网络威胁。但是,由于规则集的扩展和线路速率的不断提高,实现高速DPI仍具有挑战性。一个关键问题是有限自动机的大小超出了片上存储器的容量,从而导致昂贵的片外存储器访问。本文提出了一种基于硬件的DPI引擎,该引擎利用新颖的技术来最大限度地减少有限自动机的存储需求。我们提出一种技术,该技术使用内容寻址存储器,交错存储器组和数据打包的修改形式。性能评估结果表明,在当代的FPGA芯片中使用单个引擎可以达到高达2.5 Gbps的吞吐量。在许多情况下,单引擎方法可以比直接方法减少90%以上的内存使用。

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