A Hybrid Intelligent Learning Algorithm to Identify the ECNS Based on FBP Optimized by GA

Abstract

Along with the development of computer network, the electronic commerce has become the new pattern to carry on the commercial activity gradually, but the security problem is also getting more and more prominent. How to identify the E-commerce network security (ECNS) rating and establish a security convenient application environment for the electronic commerce has already become a major concern topic that needs to be settled urgently. To identify the ECNS rating scientifically and accurately, this paper proposes a hybrid intelligent learning algorithm which uses the genetic algorithm (GA) to optimize the fuzzy back-propagation (FBP) neural network. The algorithm not only can exert the unique advantages of BP neural network (BPNN), but also overcome the shortcoming to produce the local minimum points in the network modeling process and enhance the accuracy of network security identification greatly. The ECNS identification results for 14 E-commerce systems show that the method is reliable and efficiency.