Deep packet inspection and packet classification are the most computationally expensive operations in a Network Intrusion Detection (NID) system. Deep packet inspection involves content matching where the payload of the incoming packets is matched against a set of signatures in the database. Packet classification involves inspection of the packet header fields and is basically a multi-dimensional matching problem. Any matching in software is very slow in comparison to current network speeds. Also, both of these problems need a solution which is scalable and can work at high speeds. Due to the high complexity of these matching problems, only Field-Programmable Gate Array (FPGA) or Application-Specific Integrated Circuit (ASIC) platforms can facilitate efficient designs.
Two novel FPGA-based NID solutions were developed and implemented that not only carry out pattern matching at high speed but also allow changes to the set of stored patterns without resource/hardware reconfiguration; to their advantage, the solutions can easily be adopted by software or ASIC approaches as well. In both solutions, the proposed NID system can run while pattern updates occur. The designs can operate at 2.4 Gbps line rates, and have a memory consumption of around 17 bits per character and a logic cell usage of around 0.05 logic cells per character, which are the smallest compared to any other existing FPGA-based solution.
In addition to these solutions for pattern matching, a novel packet classification algorithm was developed and implemented on a FPGA. The method involves a two-field matching process at a time that then combines the constituent results to identify longer matches involving more header fields. The design can achieve a throughput larger than 9.72 Gbps and has an on-chip memory consumption of around 256Kbytes when dealing with more than 10,000 rules (without using external RAM). This memory consumption is the lowest among all the previously proposed FPGA-based designs for packet classification
