Granidt: Towards Gigabit Rate Network Intrusion Detection Technology
FPL '02 Proceedings of the Reconfigurable Computing Is Going Mainstream, 12th International Conference on Field-Programmable Logic and Applications
Implementation of a Content-Scanning Module for an Internet Firewall
FCCM '03 Proceedings of the 11th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
FPGA Based Network Intrusion Detection using Content Addressable Memories
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Gigabit Rate Packet Pattern-Matching Using TCAM
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Fast Regular Expression Matching Using FPGAs
FCCM '01 Proceedings of the the 9th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
A Framework for Rule Processing in Reconfigurable Network Systems
FCCM '05 Proceedings of the 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
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The overall performance of an intrusion protection system depends not only on the packet header classification and pattern matching, but also on the post-operative determination of correlative patterns of matched rules. An increasing number of patterns associated with a rule heighten the importance of correlative pattern matching. This work proposes a TCAM-based smart architecture that supports both deep pattern-matching and correlative pattern-matching. The proposed architecture overcomes the difficulties in implementing TCAM when the patterns are very deep and the rules for packet payload involve many patterns whose positions lie within a range. A real case payload is simulated using a Snort 2.3 rule set and simulation results demonstrate the feasibility of the proposed architecture in supporting a high-speed and robust intrusion detection and prevention system.