Mobile Phone Virus Detection Method Based On BP Neural Network

The popularity of mobile Internet technology and mobile intelligent terminal technology to people’s work and life brought great convenience, however mobile phone virus has emerged and quickly spread, mobile phone virus will steal user privacy information, to send text messages back, subscribe to all kinds of value-added services, endangering the interests of users and network security.Virus detection technology at present is mainly divided into two kinds of static analysis and dynamic monitoring. These two algorithms need to establish artificial virus database, and through the comparison of the virus feature code to achieve the purpose of identification of virus,low intelligence. BP neural network is a kind of error back propagation training algorithm for the multilayer feedforward network, the neural network model is one of the most widely used. BP neural network can learn and store a large number of input- output model mapping, without prior explanation of the mathematical equations describing this mapping.This is the mobile phone virus detection algorithm based on BP neural network, a significant increase in intelligence and efficiency. Through the study and experimental research, completed the following work.First of all, the mobile phone virus processing, through the anti compiler to obtain the virus module source code, and then the fragmentation of processing, through the feature code analysis method to extract the virus characteristic code information. Organize the virus type, collect the training samples and test samples.And then the BP neural network of mobile phone virus identification algorithm based on and through the MATLAB platform were simulation and training, and ultimately achieve the training effect, improve the recognition rate of the algorithm, prove the algorithm in this research is feasible, and pointed out the problems existed problems and the research direction in the future.