Abstract
Finite state automata are widely used in firewalls, data detection and content audit systems to match complex sets of regular expressions in network packets. However, with the continuous increase in the types of network contents and network traffics in recent years, the deep packet inspection systems based on finite state automata also require regular engines for less memory consumption and higher operating speed. This paper analyzes the feature and problem of finite state automata and improves non-deterministic finite automata by reducing the conversion edge to reduce the memory usage. The experiment results which are made by real-world dataset show that the memory usage is reduced more than half.
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