Efficient Regular Expression Matching and Hardware-Accelerated Finite Automata Pattern Recognition in NIDS

To protect network infrastructure from the ever-changing cyber threats, Intrusion Detection Systems (IDS) perform important duties. This study introduces a sophisticated algorithm aimed at overcoming key challenges in IDS. These challenges include efficient regular expression matching, hardware implementation, and improved pattern recognition. The algorithm employs a unique technique to reduce memory specifications by using controlled faults into the pattern matching process. It builds upon perfect hashing, ensuring precise and efficient regular expression matching, making it ideal for high-speed processing in IDS applications. Additionally, the central component of a hardware-based Network Intrusion Detection System (NIDS), the technique comprises a signature match processor that is based on a field-programmable gate array (FPGA). For effective string matching, this processor makes use of a CAM-based cellular architecture. For multiple signature matches, it generates priority-encoded addresses using a binary tree structure. To enhance IDS capabilities further, the algorithm introduces an efficient method for detecting regular expression matches within network traffic text using Field-Programmable Gate Arrays (FPGAs). It presents a hardware implementation approach based on Deterministic Finite Automata (DFA), enhancing both speed and accuracy in pattern matching. This proposed algorithm provides a comprehensive solution to optimize intrusion detection by integrating innovative techniques in regular expression matching, hardware acceleration, and pattern recognition, thereby enhancing network security against springing cyber threats.