String searching algorithms
End-to-end internet packet dynamics
IEEE/ACM Transactions on Networking (TON)
Packet reordering is not pathological network behavior
IEEE/ACM Transactions on Networking (TON)
Specialized Hardware for Deep Network Packet Filtering
FPL '02 Proceedings of the Reconfigurable Computing Is Going Mainstream, 12th International Conference on Field-Programmable Logic and Applications
Assisting Network Intrusion Detection with Reconfigurable Hardware
FCCM '02 Proceedings of the 10th 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
FTSE: The FNP-Like TCAM Searching Engine
ISCC '05 Proceedings of the 10th IEEE Symposium on Computers and Communications
Efficient Packet Matching for Gigabit Network Intrusion Detection using TCAMs
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 01
| Hi-index | 0.01 |
In this paper, we propose a novel algorithm for pattern matching at multi gigabit network. It is called as the IPM. Our proposed algorithm can minimize the system overhead which is generated to extract patterns at out-ofsequence packets since the IPM does not require a buffering, reordering and reassembling to keep sequence of packets. Our proposed algorithm performs independently partial pattern matching to extract the pattern from incoming multiple packets at multi gigabit network. The IPM is implemented by FPGA, TCAM and SRAM. Consequently, we show the IPM can reduce 87% of TCAM entries to extract 17 bytes pattern and w=4. Moreover, we observed that IPM can perform the scanning of packets at 10.941Gbps and it spent 5.79LC/Char to implement the IPM. Then, we achieved the 1.89 Gbps/LC of PUC score. This means that IPM provides the optimal performance in contrast with hardware complexity. Therefore, we propose the cost-effective algorithm to extract the pattern at multi gigabit network.