A fast string searching algorithm
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Longest prefix matching using bloom filters
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Implementation Results of Bloom Filters for String Matching
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
A High Throughput String Matching Architecture for Intrusion Detection and Prevention
Proceedings of the 32nd annual international symposium on Computer Architecture
Fast and scalable pattern matching for content filtering
Proceedings of the 2005 ACM symposium on Architecture for networking and communications systems
Longest prefix matching using bloom filters
IEEE/ACM Transactions on Networking (TON)
High performance dictionary-based string matching for deep packet inspection
INFOCOM'10 Proceedings of the 29th conference on Information communications
Proceedings of the 5th ACM/IEEE Symposium on Architectures for Networking and Communications Systems
Fast and Scalable Pattern Matching for Network Intrusion Detection Systems
IEEE Journal on Selected Areas in Communications
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Pattern-matching techniques have recently been applied to network security applications such as intrusion detection, virus protection, and spam filters. The widely used Aho-Corasick (AC) algorithm can simultaneously match multiple patterns while providing a worst-case performance guarantee. However, as transmission technologies improve, the AC algorithm cannot keep up with transmission speeds in high-speed networks. Moreover, it may require a huge amount of space to store a two-dimensional state transition table when the total length of patterns is large. In this paper, we present a pattern-matching architecture consisting of a stateful pre-filter and an AC-based verification engine. The stateful pre-filter is optimal in the sense that it is equivalent to utilizing all previous query results. In addition, the filter can be easily realized with bitmaps and simple bitwise-AND and shift operations. The size of the two-dimensional state transition table in our proposed architecture is proportional to the number of patterns, as opposed to the total length of patterns in previous designs. Our proposed architecture achieves a significant improvement in both throughput performance and memory usage.