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Collaboration loT-Based RBAC with Trust Evaluation Algorithm Model for Massive IoT Integrated Application

机译:基于协作loT的RBAC与信任评估算法模型在大规模物联网集成应用中的应用

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摘要

With the recent advances in ubiquitous communications and the growing demand for low-power wireless technology, smart IoT device (SID) to access various Internet of Things (IoT) resources through Internet at any time and place alternately. There are some new requirements for integration IoT servers in which each one is individually gathering its local resources in Internet, which cooperatively supports SID to get some flexibility or temporary contract(s) and privileges in order to access their corresponding desired service(s) in a group of collaboration IoT servers. However, traditional access control schemes designed for a single server are not sufficient to handle such applications across multiple collaboration IoT servers to get rich services in IoT environments. It does not take into account both security and efficiency of IoT servers, which securely share their resources. Therefore, the collaboration IoT-based RBAC (Role-based Access Control) with trust evaluation (TE) algorithm model to reducing internal security threats in intra-server and inter server for the massive IoT integrated application is proposed in this paper. Finally, the three trust evaluation algorithms including a local trust evaluation algorithm, a virtual trust evaluation algorithm and a cooperative trust evaluation algorithm in the proposed collaboration IoT-based RBAC model, which are designed and presented for reducing internal security threats in collaborative IoT servers.
机译:随着无处不在通信的最新进展以及对低功耗无线技术的需求不断增长,智能物联网设备(SID)可以随时随地通过Internet交替访问各种物联网(IoT)资源。集成物联网服务器有一些新要求,其中每个人都在Internet上单独收集其本地资源,这些要求共同支持SID以获取一些灵活性或临时合同和特权,以便在其中访问其相应的所需服务。一组协作物联网服务器。但是,为单个服务器设计的传统访问控制方案不足以在多个协作IoT服务器之间处理此类应用程序,以在IoT环境中获得丰富的服务。它没有同时考虑安全共享其资源的IoT服务器的安全性和效率。因此,本文提出了一种基于物联网的基于角色的访问控制(RBAC)与信任评估(TE)算法模型,以减少大规模物联网集成应用服务器内部和服务器之间的内部安全威胁。最后,在提出的基于协作物联网的RBAC模型中,设计并提出了三种信任评估算法,包括本地信任评估算法,虚拟信任评估算法和协作信任评估算法,旨在减少协作IoT服务器中的内部安全威胁。

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