一种面向物联网的产消者选择博弈方法

ANovel Game Theoretical Security Method for the Internet of Things

物联网中攻击者由于知道和用户相同的安全测试信息,能够得知哪些产消者更受用户青睐并集中攻击。提出了一种新的非协作、双玩家的决策支持方法—产消者选择博弈(Prosumers Selection Game,PSG),PSG采用纳什均衡确定了最优化用户报酬的产消者子集。该方法使用纳什玩家选择(Nash Prosumer Selection,NPS)得到产消者子集概率向量的博弈解,并且用户将面临最小期望损害。此外,用户使用NPS选择产消者,依然有非0概率选择出最不安全的产消者。最后将PSG方法中的NPS和两种不同的启发式选择算法进行仿真比较,结果表明NPS在降低安全风险方面能够获得约38%的性能提升。

In IoT, because of knowing the same information of security measures as users, the attacker can know the preferable prosumers and attack them intensively. Hence, a novel non-cooperative, two-player decision-support method called prosumer selection game （PSG） is proposed, and the Nash Equilibria is used to decide subsets of prosumer optimizing users＇ payoffs. The proposed PSG derives the game solution by using Nash prosumers selection （NPS）, and the solution is a probability vector over subsets of prosumers. When using NPS, a user confronts the least expected damages. PSG still has a non-zero probability to select the least secure prosumer by using NPS. Finally, PSG is compared to two traditional heuristic algorithms by simulation. The simulation results demonstrate that, the proposed PSG has a 38 % security-risk mitigation improvement than other algorithms.