Abstract
Pattern or string matching algorithm is one of the most critical tasks in the design of a high-speed network intrusion detection system (NIDS). In this paper, an efficient pre-filtering algorithm, called Super-Symbol Filter (SSF), is proposed to filter the normal traffic before they are forwarded to a pattern matching algorithm. The proposed SSF algorithm uses a tiny data structure, and is light-computational and cache- resident. It can be implemented efficiently in a software-based platform. Experimental results show that with Snort's patterns, the computation time of the SSF with the AC algorithm to process the Defcon9 trace is only one-third to half of that of a pure AC algorithm. Thus, the speed gain of the proposed scheme is around 100-300 %.
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