Abstract
Currently, signature-based network intrusion detection systems (NIDSs) have been widely deployed in various organizations such as universities and companies aiming to identify and detect all kinds of network attacks. However, the big suffering problem is that signature matching in these detection systems is too expensive to their performance in which the cost is at least linear to the size of an input string and the CPU occupancy rate can reach more than 80 percent in the worst case. This problem is a key limiting factor to encumber higher performance of a signature-based NIDS under a large-scale network. In this paper, we developed an exclusive signature matching scheme based on single character frequency to improve the efficiency of traditional signature matching. In particular, our scheme calculates the single character frequency from both stored and matched NIDS signatures. In terms of a decision algorithm, our scheme can adaptively choose the most appropriate character for conducting the exclusive signature matching in distinct network contexts. In the experiment, we implemented our scheme in a constructed network environment and the experimental results show that our scheme offers over-all improvements in signature matching.KeywordsIntrusion detectionSignature matchingIntelligent systemNetwork security
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