An Efficient Memory Architecture For Network Intrusion Detection Systems Using Pattern Partitioning And Parallel String Matching

Due to the advantages of easy re-configurability and scalability, the memory-based string matching architecture is widely adopted by network intrusion detection systems (NIDS).The ability to inspect both packet headers and payloads to identify attack signatures makes network intrusion detection system (NIDS) a promising approach to protect Internet systems. In this paper, we propose a memory-efficient pattern-matching algorithm which can significantly reduce the memory requirement. Using the pattern dividing, the variety of target pattern lengths can be mitigated, so that memory usage in homogeneous string matchers can be efficient. In order to identify each original long pattern being divided, a two-stage sequential matching scheme is proposed for the successive matches with sub-patterns. We synthesized this design using Quartus II 11.0 version.