雾计算中的模糊信任管理方法

Masooma Muhammad Nabi, M. A. Shah
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引用次数: 1

摘要

物联网(IoT)技术已经彻底改变了世界,任何东西都可以智能连接和访问。物联网利用云计算来处理和存储大量数据。在某种程度上,雾计算的概念已经出现在云和物联网设备之间,以解决延迟问题。当雾节点交换数据以完成特定任务时,存在许多安全和隐私风险。例如,将数据卸载到恶意雾节点可能导致非法收集或修改用户的私有数据。在本文中,我们依靠信任来检测和分离坏雾节点。我们使用Mamdani模糊方法,并考虑具有许多雾服务器的医院场景。目的是识别恶意雾节点。延迟和距离等指标用于评估每个雾服务器的可信度。本研究的主要贡献在于确定模糊逻辑配置如何改变雾节点的信任值。实验结果表明,该方法能够在给定场景下检测出坏雾装置并建立其可信度。
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A Fuzzy Approach to Trust Management in Fog Computing
The Internet of Things (IoT) technology has revolutionized the world where anything is smartly connected and is accessible. The IoT makes use of cloud computing for processing and storing huge amounts of data. In some way, the concept of fog computing has emerged between cloud and IoT devices to address the issue of latency. When a fog node exchanges data for completing a particular task, there are many security and privacy risks. For example, offloading data to a rogue fog node might result in an illegal gathering or modification of users' private data. In this paper, we rely on trust to detect and detach bad fog nodes. We use a Mamdani fuzzy method and we consider a hospital scenario with many fog servers. The aim is to identify the malicious fog node. Metrics such as latency and distance are used in evaluating the trustworthiness of each fog server. The main contribution of this study is identifying how fuzzy logic configuration could alter the trust value of fog nodes. The experimental results show that our method detects the bad fog device and establishes its trustworthiness in the given scenario.
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