依赖小波神经网络算法的信息安全风险评估方法

Information security risk assessment method based on wavelet neural network algorithm

文中针对信息安全风险评估过程中集合信息存在的虚假相关问题,采用传统的方法很难将其收敛到状态空间的最优解,导致出现评估性能不佳。文中利用小波神经网络算法进行信息安全风险评估。在随机泛函的学习样本约束下,求解小波神经网络算法的最优解。研究结果表明:采用小波神经网络算法可以有效解决集合信息存在的虚假相关,从而避免对显变量的影响,更能有效提高信息安全风险评估精度。

In order to solve the false related problems in the information security risk assessmentprocess, it is difficult to converge to the optimal solution of the state space by the traditional method,which leads to the poor performance of the evaluation. In this paper, wavelet neural network algorithm isapplied to risk assessment of information security. Under the constraint of learning samples of stochasticfunctional, the optimal solution of wavelet neural network algorithm is obtained. The results show that thewavelet neural network algorithm can effectively solve the false and false correlation of the collectioninformation, thus avoiding the influence on the more explicit variables, and can effectively improve theaccuracy of information security risk assessment.