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A two-way trust management system for fog computing

机译:雾计算的双向信任管理系统

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Fog computing is the next frontier of cloud computing since it can compute and store a massive amount of data generated by IoT devices near their sources. Indeed, transmitting all these data to the cloud will take up a huge amount of bandwidth. However, its features and flexibility of deployment make fog computing vulnerable to security and privacy attacks. The high-mobility support, dynamic environment, geographical distribution, location awareness, proximity to end users, and lack of redundancy are among these features that make the existing schemes not adequate to fog computing. Therefore, since trust management ensures security and privacy, we propose a two-way subjective logic-based trust management system that enables a service requester to verify whether a service provider can give reliable and secure services and lets the service provider check the trustworthiness of the service requester. Extensive evaluation of the system shows that the trust value of a node is accurate and converges in a very few trust computation cycles. The solution is also resilient to a large population of misbehaving nodes and it is able to thwart trust-based attacks successfully. Moreover, comparative analysis is made with different modification of the system and two baseline schemes, PeerTrust and EigenTrust. The comparison depicts that the two-way trust management proposals have lower overhead, allow a balanced load distribution, are effective in selecting the right service providers and are more accurate than the conventional one-way trust management systems.
机译:雾计算是云计算的下一个前沿领域,因为它可以计算和存储由物联网设备在其源附近生成的大量数据。实际上,将所有这些数据传输到云将占用大量带宽。但是,它的功能和部署的灵活性使雾计算容易受到安全和隐私攻击。这些特点使现有的方案不足以进行雾计算,而高机动性的支持,动态的环境,地理分布,位置意识,与最终用户的距离以及冗余的缺乏等都是这些特征。因此,由于信任管理可确保安全性和隐私性,因此我们提出了一种基于双向主观逻辑的信任管理系统,该系统可使服务请求者验证服务提供者是否可以提供可靠和安全的服务,并让服务提供者检查服务提供者的信任度。服务请求者。对系统的广泛评估表明,节点的信任值是准确的,并且会在很少的信任计算周期内收敛。该解决方案还可以抵抗大量行为异常的节点,并且能够成功挫败基于信任的攻击。此外,对系统进行了不同的修改并使用了两个基线方案PeerTrust和EigenTrust进行了比较分析。比较表明,双向信任管理建议具有较低的开销,允许均衡的负载分配,有效地选择合适的服务提供商并且比常规的单向信任管理系统更准确。

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