Since frequent communication between applications takes place in high speed networks,\ndeep packet inspection (DPI) plays an important role in the network application awareness.\nThe signature-based network intrusion detection system (NIDS) contains a DPI technique that\nexamines the incoming packet payloads by employing a pattern matching algorithm that dominates\nthe overall inspection performance. Existing studies focused on implementing efficient pattern\nmatching algorithms by parallel programming on software platforms because of the advantages of\nlower cost and higher scalability. Either the central processing unit (CPU) or the graphic processing\nunit (GPU) were involved. Our studies focused on designing a pattern matching algorithm based on\nthe cooperation between both CPU and GPU. In this paper, we present an enhanced design for our\nprevious work, a length-bounded hybrid CPU/GPU pattern matching algorithm (LHPMA). In the\npreliminary experiment, the performance and comparison with the previous work are displayed,\nand the experimental results show that the LHPMA can achieve not only effective CPU/GPU\ncooperation but also higher throughput than the previous method.
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