Author(s): WANG Hai-yan, Department of Information Engineering, Binzhou University
Pages: 166-169+173
Year: 2016 Issue:  2
Journal: Journal of Inner Mongolia Normal University(Natural Science Edition)
Keyword:  information system; gray relation analysis; neural network; risk assessment;
Abstract: In order to improve the accuracy of information security risk assessment,this paper puts forward a novel information security risk assessment model based on grey relation analysis and neural network.First of all,index system of information security risk evaluation is built,and secondly,grey relation analysis method is used to analyze relation between the evaluation index to remove some redundant evaluation indexes,finally,RBF neural network is used to establish information security risk assessment model and the performance of security risk evaluation is test by an enterprise information system.The results show that the proposed model can remove useless evaluation indexes to reduces the number of input vectors for RBF neural network,improve the efficiency,and assessment accuracy is higher than that other models.