Risk Analysis of the Information System by Using Factor Analysis and Support Vector Machine

Risk assessment is the key technology in information system management. In view of the risk factors characteristics of small sample, time variability, etc., a risk assessment method (FA-CS-SVM) for the information system by using factor analysis and improved support vector machine is proposed to improve the accuracy of risk assessment. Firstly, factor analysis method is used to deal with the risk index system to extract the public index system and eliminate the correlation among the indexes, and secondly public indexes are used as input vector of support vector machine for training which cuckoo search algorithm is used to find the most reasonable parameters for support vector machine, and the risk evaluation model of information system is constructed, and the feasibility and rationality of the model is verified in the end. The results show that FA-CS-SVM can improve the accuracy of the information system risk evaluation, and the evaluation results can provide scientific reference for the management of information system.