Accelerating string matching using multi-threaded algorithm on GPU

Network Intrusion Detection System has been widely used to protect computer systems from network attacks. Due to the ever-increasing number of attacks and network complexity, traditional software approaches on uni-processors have become inadequate for the current high-speed network. In this paper, we propose a novel parallel algorithm to speedup string matching performed on GPUs. We also innovate new state machine for string matching, the state machine of which is more suitable to be performed on GPU. We have also described several speedup techniques considering special architecture properties of GPU. The experimental results demonstrate the new algorithm on GPUs achieves up to 4,000 times speedup compared to the AC algorithm on CPU. Compared to other GPU approaches, the new algorithm achieves 3 times faster with significant improvement on memory efficiency. Furthermore, because the new Algorithm reduces the complexity of the Aho-Corasick algorithm, the new algorithm also improves on memory requirements.