基于量子神经网络的信息安全风险评估方法  

Information Security Risk Assessment Method Based on Quantum Neural Network

作　　者：罗辉[1] 潘平[1] 李换双[1] 

机构地区：[1]贵州大学计算机科学与信息学院

出　　处：《贵州大学学报（自然科学版）》2013年第1期74-78,共5页Journal of Guizhou University:Natural Sciences

基　　金：教育部信息安全类教育科学改革项目(NO:JWZ201011);贵州省科学技术基金项目(黔科合J字[2012]2132号)

摘　　要：针对信息安全风险评估对象的多样性和信息的不确定性、数据量大以及无规律性的特点,提出基于量子神经网络的信息安全风险评估方法。将实际检测的对象属性作为量子神经网络的输入,经量子神经网络系统处理,获得信息系统的综合风险。实验仿真结果表明:基于量子神经网络的风险评估方法比经典BP网络评估方法更有效、可靠,可以应用于实际的信息安全风险评估中。For the problem of the features of the diversity of objects which belongs to the security risk assessment of information and the uncertainty, large volumes of data and no regularity of information, the information security risk assessment methods were proposed based on Quantum Neural Networks. The object properties were treated as the entrance of Quantum Neural Networks, and the integrated risk of information system was obtained through the processing of Quantum Neural Networks system. Simulation results show that risk assessment methods based on Quantum Neural Networks are more efficient and reliable than the classical BP network assessment methods and they can be applied to the actual the security risk assessment of information.

关 键 词：量子神经网络 BP神经网络 信息安全 风险评估 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]