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Trust Evaluation for Light Weight Security in Sensor Enabled Internet of Things: Game Theory Oriented Approach

机译:启用传感器的物联网中轻量级安全性的信任评估:面向博弈论的方法

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In sensor-enabled Internet of Things (IoT), nodes are deployed in an open and remote environment, therefore, are vulnerable to a variety of attacks. Recently, trust-based schemes have played a pivotal role in addressing nodes' misbehavior attacks in IoT. However, the existing trust-based schemes apply network wide dissemination of the control packets that consume excessive energy in the quest of trust evaluation, which ultimately weakens the network lifetime. In this context, this paper presents an energy efficient trust evaluation (EETE) scheme that makes use of hierarchical trust evaluation model to alleviate the malicious effects of illegitimate sensor nodes and restricts network wide dissemination of trust requests to reduce the energy consumption in clustered-sensor enabled IoT. The proposed EETE scheme incorporates three dilemma game models to reduce additional needless transmissions while balancing the trust throughout the network. Specially: 1) a cluster formation game that promotes the nodes to be cluster head (CH) or cluster member to avoid the extraneous cluster; 2) an optimal cluster formation dilemma game to affirm the minimum number of trust recommendations for maintaining the balance of the trust in a cluster; and 3) an activity-based trust dilemma game to compute the Nash equilibrium that represents the best strategy for a CH to launch its anomaly detection technique which helps in mitigation of malicious activity. Simulation results show that the proposed EETE scheme outperforms the current trust evaluation schemes in terms of detection rate, energy efficiency and trust evaluation time for clustered-sensor enabled IoT.
机译:在启用传感器的物联网(IoT)中,节点部署在开放和远程环境中,因此容易受到各种攻击。最近,基于信任的方案在解决物联网中节点的不良行为攻击方面发挥了关键作用。但是,现有的基于信任的方案对控制包进行网络范围的分发,这些控制包在寻求信任评估时会消耗过多的能量,最终会削弱网络的寿命。在这种情况下,本文提出了一种节能信任评估(EETE)方案,该方案利用分层信任评估模型来缓解非法传感器节点的恶意影响,并限制信任请求在网络范围内的传播,以减少集群传感器的能耗。启用物联网。拟议的EETE方案结合了三个困境博弈模型,以减少额外的不必要传输,同时平衡整个网络的信任度。特别是:1)集群形成游戏,将节点提升为集群头(CH)或集群成员,以避免多余的集群; 2)最佳集群形成困境博弈,用于确定用于维持集群中信任平衡的最小信任建议数; 3)基于活动的信任困境博弈,用于计算纳什均衡,这代表CH发起其异常检测技术的最佳策略,该技术有助于缓解恶意活动。仿真结果表明,提出的EETE方案在支持群集传感器的IoT的检测率,能效和信任评估时间方面均优于当前的信任评估方案。

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