基于模糊集和粗糙集理论的云安全评价模型  

Model of Cloud Security Evaluation Based on Rough Set and Fuzzy Set Theory

作　　者：唐国纯[1] 赵竞雄[2] 

机构地区：[1]琼台师范高等专科学校信息技术系,海口571100 [2]电子科技大学数学科学学院,成都610054

出　　处：《科技通报》2015年第10期115-117,共3页Bulletin of Science and Technology

基　　金：海南省自然科学基金资助(614247);中央高校基本科研业务费资助(3142014069)

摘　　要：研究对云安全的综合评价模型,提高云计算中的网格计算并行处理和防病毒攻击能力。传统的云安全评价模型采用多层模糊集自适应算法,评价系统单一,抗病毒攻击能力较差。提出一种基于模糊集和粗糙集理论的云安全评价模型,构建云安全数据信息网格计算系统,进行安全动态数据流分析,采用基于模糊集和粗糙集理论的评价模型,构建有格点链重叠检测和向量化运算算法,检测病毒入侵信号。仿真结果表明,该云安全综合评价模型执行效率较高,对病毒入侵的检测能力提高,安全检测的成功率比传统方法提高34%,该模型有较好的安全综合评价和攻击入侵检测性能。在云计算系统安全构架中具有较好的应用价值。The comprehensive evaluation of the cloud security research model, improve the calculation of parallel process-ing and anti-virus attack ability of cloud computing in grid. Cloud security evaluation model using the traditional multilay-er fuzzy set adaptive algorithm, evaluation system is single, antiviral attack ability is bad. Presents a kind of fuzzy set and rough set safety evaluation model based on cloud theory, cloud security data information construction of grid computing sys-tem, security of dynamic data flow analysis, using fuzzy set theory and rough set based on the evaluation model, build a lat-tice chain overlap detection and vectorization algorithm, detection of virus intrusion signal. Simulation results show that the higher efficiency of the execution of the cloud security comprehensive evaluation model, improve the ability of detecting vi-rus invasion, safety detection and improve the success rate of 34%compared with the traditional method, the comprehen-sive evaluation model for better safety and attack intrusion detection performance. In the cloud computing has good value of application system security framework.

关 键 词：模糊集 粗糙集理论 云安全 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]