Design and Security Verification of Network Intrusion Detection System Based on Multi‐Strategy Improved <scp>WOA</scp>

ABSTRACT Network security is becoming increasingly severe due to the rapid advancement of information technology. Traditional network intrusion detection systems exhibit issues such as insufficient accuracy and efficiency in detecting new attacks and processing large amounts of data. Therefore, a network intrusion detection system based on multi‐strategy improved Whale Optimization Algorithm (WOA) is built to enhance the accuracy, efficiency, and adaptability of intrusion detection to complex network environments. This study improves the initial solution quality of the population through reverse learning strategy, balances global exploration and local development capabilities, and expands the optimization range using enhanced search strategy. The detection accuracy increased from 89.16% to 96.83%, the inference time decreased from 1.97 s to 1.77 s, the F1 score added from 0.87 to 0.93, and the false negative rate significantly declined. The research method improves the accuracy and efficiency and also enhances the robustness to deal with complex network attacks. The network intrusion security system can more accurately identify normal traffic and various attack behaviors in the network, judge network requests in a shorter time, and timely prevent attacks from entering the network, providing efficient and reliable solutions for network security protection.