Research of Information Security Risk Management Based on Statistical Learning Theory
Zhao Li, Yongchun Wu, Wu Xuexia · 2009
Traditional methods used in the information security risk management are mostly based on the statistics, their validity of application are limited to large sample situations, while the statistical learning theory is introduced to the innovation of information security management, its structural risk minimization principle and from which the support vector machine developed offer new theory basis for predicting the security risk and achieve the minimal risk. This paper not only detailedly discusses the structural risk minimization principle and from which the support vector machine developed offer new theory basis for predicting the security risk and achieve the minimal risk, but also puts forwards the idea of using structural risk minimization principle and the support vector machine in information security risk management, which provides the brand-new mentality to the information security risk management.