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针对现有蜜罐易被攻击者识破而导致其抵御渗透攻击时经常失效的问题,提出一种基于动态伪装网络的主动欺骗防御方法。首先,给出动态伪装网络定义并描述基于动态伴随网络的主动欺骗攻防场景;然后,在分析攻防交互过程的基础上,构建信号博弈模型来指导最优欺骗策略选取;进一步,设计基于双层威胁渗透图的攻防策略收益量化方法;最后,提出一种统一纯策略与混策略的博弈均衡求解方法。实验结果表明,基于动态伪装网络,精炼贝叶斯均衡能够为防御者实施最优防御策略提供有效指导,实现防御者收益最大化。此外,还总结了利用动态伪装网络进行主动欺骗防御的特点与规律。 相似文献
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基于隐马尔可夫模型的资源滥用行为检测方法研究 总被引:2,自引:0,他引:2
针对信息系统中内部人员的资源滥用行为, 已有的检测方法要么不能有效检测新的资源滥用行为, 要么需要获得资源滥用行为的先验知识, 因而这些检测方法在应用中严重限. 本文提出了一种基于隐马尔可夫模型(HMM)的内部人员资源滥用行为检测方法. 该模型以信息系统的敏感文件夹作为模型的状态, 以用户的事务处理操作作为观测符号, 采用Baum-Welch算法确定模型参数; 基于该模型建立内部人员访问行为的HMM模型, 并用于资源滥用行为检测. 仿真结果表明了该检测方法的有效性. 相似文献
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To solve the slow congestion detection and rate convergence problems in the existing rate control based fair data collection schemes, a new fair data collection scheme is proposed, which is named the improved scheme with fairness or ISWF for short. In ISWF, a quick congestion detection method, which combines the queue length with traffic changes of a node, is used to solve the slow congestion detection problem, and a new solution, which adjusts the rate of sending data of a node by monitoring the channel utilization rate, is used to solve the slow convergence problem. At the same time, the probability selection method is used in ISWF to achieve the fairness of channel bandwidth utilization. Experiment and simulation results show that ISWF can effectively reduce the reaction time in detecting congestion and shorten the rate convergence process. Compared with the existing tree-based fair data collection schemes, ISWF can achieve better fairness in data collection and reduce the transmission delay effectively, and at the same time, it can increase the average network throughput by 9.1% or more. 相似文献