ClusterFA: a memory-efficient DFA structure for network intrusion detection

Authors:
Lei Jiang;Jianlong Tan;Yanbing Liu
Affiliations:
Chinese Academy of Sciences, Beijing, P. R. China;Chinese Academy of Sciences, Beijing, P. R. China;Chinese Academy of Sciences, Beijing, P. R. China
Venue:
Proceedings of the 7th ACM Symposium on Information, Computer and Communications Security
Year:
2012

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Abstract

Network intrusion detection systems (NIDS) plays an increasing important role in the field of network security. Current NIDS, such as Bro and Snort, mainly use signatures to represent and detect networking attacks. Traditionally the signatures are depicted by exact string patterns. However, new worms and viruses emerge endlessly in recent years. As a result, the scale of signatures increases sharply. Compared with exact strings, regular expressions have more powerful expressiveness, and are replacing exact strings gradually in state-of-the-art NIDS.