CompactDFA: Generic State Machine Compression for Scalable Pattern Matching
Source: Columbia University
Pattern matching algorithms lie at the core of all contemporary Intrusion Detection Systems (IDS), making it intrinsic to reduce their speed and memory requirements. This paper focuses on the most popular class of pattern-matching algorithms, the Aho-Corasick - like algorithms, which are based on constructing and traversing a Deterministic Finite Automaton (DFA), representing the patterns. While this approach ensures deterministic time guarantees, modern IDSs need to deal with hundreds of patterns, thus requiring to store very large DFAs which usually do not fit in fast memory. This results in a major bottleneck on the throughput of the IDS, as well as its power consumption and cost.