Performance in Practice of String Hashing Functions
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
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
Journal of Algorithms
Scalable Pattern Matching for High Speed Networks
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Pre-Decoded CAMs for Efficient and High-Speed NIDS Pattern Matching
FCCM '04 Proceedings of the 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Fast Reconfiguring Deep Packet Filter for 1+ Gigabit Network
FCCM '05 Proceedings of the 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
A precise analysis of Cuckoo hashing
ACM Transactions on Algorithms (TALG)
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Pattern matching for network intrusion/prevention detection demands exceptionally high throughput with recent updates to support new attack patterns. This paper describes a novel FPGA-based pattern matching architecture using a recent hashing algorithm called Cuckoo Hashing. The proposed architecture features on-the-fly pattern updates without reconfiguration, more efficient hardware utilization, and higher throughput. Through various algorithmic changes of Cuckoo Hashing, we can implement parallel pattern matching on SRAM-based FPGA. Our system can accommodate the newest Snort rule-set, an open source Network Intrusion Detection/Prevention System, and achieve the highest utilization in terms of SRAM per character and Logic Cells per character at 15.63 bits/character and 0.033 Logic Cells/character, respectively on major Xilinx Virtex FPGA architectures. Compared to others, ours is more efficient than any other Xilinx FPGA architectures.