Risk Assessment of Information Security Based on Quantum Gate Circuit Neural Networks
摘要
Information security risk assessment is a process of comprehensive evaluation of uncertain and random potential risks in order to effectively suppress and transfer systemic risks.On the basis of analyzing the security elements and security system of information system,the information security risk assessment model based on information assets is constructed.Through the risk assessment index system,the attributes of the evaluation objects actually are obtained.The neural network model is constructed by using a set of quantum gate circurit.The normalized processing result of the attribute samples of the evaluation object is used as the network input and expressed by the quantum bit.The phase rotation is performed by the quantum revolving gate and the quenching of the quantum bit is controlled.After being processed by the network,the comprehensive risk of the evaluated object is obtained.The experimental results show that compared with the traditional BP neural network,this method can realize the risk assessment of information systems,with better convergence performance and more accurate risk prediction ability,which can provide a reliable theoretical basis for risk management.