3.2 Optimization Algorithm to cluster the network network’s optimization by genetic algorithms, we intrusion data combine them with FCM algorithm to deal with Intrusion detection cluster uses FCM and BP which intrusion data, making the ability of processing the optimized with GA. The flowchart of the process is Network intrusion data significantly improved. And shown in . we have improved the accuracy and stability of the

doi:10.1201/b18660-13

Chapter

3.2 Optimization Algorithm to cluster the network network’s optimization by genetic algorithms, we intrusion data combine them with FCM algorithm to deal with Intrusion detection cluster uses FCM and BP which intrusion data, making the ability of processing the optimized with GA. The flowchart of the process is Network intrusion data significantly improved. And shown in . we have improved the accuracy and stability of the

Chapter

ABSTRACT

FCM has a great influence on results by the selection of the initial cluster centers. BP has strong local searching ability, but it is easy to fall into local minimum. GA is a self-adaptive, global optimization, and implicit parallelism, but the local search capability is not strong. Through the introduction of the foregoing and BP neural network’s optimization by genetic algorithms, we combine them with FCM algorithm to deal with intrusion data, making the ability of processing the Network intrusion data significantly improved. And we have improved the accuracy and stability of the intrusion data clustering results.