【摘要】 为评估恶意程序传播环境中的传感网可靠度,引入"死亡"状态扩展了传统的SEIR传染病模型,采用马尔可夫链确切地描述了传感节点的状态动态变化过程.利用随机博弈,提出了传感网恶意程序传播检测模型来预测恶意程序的传播行为概率,再将得到的结果整合到马尔可夫链的状态转换矩阵,实现了恶意程序传播故意性和马尔可夫链随机性的关联.建立了利用马尔可夫链计算恶意程序传播环境中传感节点可靠度的公式,分别给出了具有星形和簇状拓扑结构的传感网可靠度评估方法.实验给出了恶意程序传播对传感节点可靠度的影响,结果表明所提出的方法能有效评估整个传感网的可靠度.更多还原

【Abstract】 To evaluate the reliability of WSNs( Wireless Sensor Networks) in the malware spread scenario, the traditional epidemic model SEIR was extended by introducing a state"Dead"and the dynamic change process of sensor node states was exactly described by a Markov chain( MC). Using the stochastic game,a malware spread detection model for WSNs was proposed to predict the probability of malware adopting the spread behavior. The prediction results attained were integrated into the MC’s state transition matrix in order to relate the malware intention to the MC randomness. An equation to compute a sensor node’s reliability in the malware spread scenario was constructed via the MC, and reliability evaluation methods for WSNs with star or cluster topology were given. Experiments have shown the influence of malware’s spread on sensor nodes’ reliability and illustrated that the proposed method can efficiently evaluate the WSNs reliability.更多还原