基于QPSO-BP的云平台信息系统安全风险分析

Security Risk Analysis of Cloud Platform Information System Based on QPSO-BP

云平台是云计算服务的重要载体,具有更开放、虚拟化、高度集成以及平台架构复杂等特性,更易受到各种威胁。论文在分析云平台架构及其服务模式的基础上,提出基于云平台信息系统的风险分析模型,引入量子粒子群优化BP神经网络(QPSO-BP)模型对信息系统安全风险进行分析,通过分析各风险因素对系统风险的影响,获得云平台风险因素敏感度评价,实现对风险的预测和管理。仿真表明,该方法能有效预测云平台信息系统风险,与GA-BP和PSO-BP神经网络预测方法相比有较好的网络性能和预测精度,为云平台信息系统风险管理提供一种科学有效的理论方法。

Cloud platform is an important carrier of cloud computing services, which is more open, virtualized, highly integrated and complex in platform architecture. It is more vulnerable to various threats. Based on the analysis of cloud platform architecture and its service mode, this paper puts forward a risk analysis model based on cloud platform information system and introduces QPSO-BP model to analyze information system security risk. By analyzing the influence of various risk factors on system risk, the sensitivity evaluation of cloud platform risk factors is obtained, the risk prediction and management are realized. Simulation results show that this method can effectively predict the risk of cloud platform information system. Compared with GA-BP and PSO-BP neural network prediction methods, it has better network performance and prediction accuracy, provides a scientific and effective theoretical method for risk management of cloud platform information system.