物联网和雾计算范例的安全和隐私

A. Rauf, R. Shaikh, Asadullah Shah
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引用次数: 19

摘要

在过去的十年中,小型化(微处理器,电池,相机等)和新型传感器制造的革命导致了基于智能对象的新应用制度,称为物联网。大多数这样的应用程序或服务是为了简化人们的生活和/或在自动化环境中设置有效的流程。然而,这种便利带来了与数据安全和人类隐私相关的新挑战。物联网中的对象是资源受限的设备,无法实现万无一失的安全框架。这些终端设备就像眼睛和耳朵一样与物理世界互动,并收集数据进行分析,以做出权宜之计。收集的数据的存储和分析是使用云计算远程完成的。将数据从物联网传输到计算云可能会带来隐私问题和网络延迟。一些应用程序需要实时决策,不能容忍网络中的延迟和抖动。在这里,边缘计算或雾计算通过在终端设备附近提供类似云的设施来解决上述问题。在本文中,我们讨论了物联网、雾计算、物联网与雾计算之间的关系、它们的安全问题以及不同研究人员的解决方案。我们总结了与该范式的每一层相关的攻击面,这将有助于提出新的安全解决方案,以提高最终用户的可接受性。我们还提出了一种基于风险的智能医疗环境信任管理模型,以应对这种高度不可预测的异构生态系统中的安全和隐私相关问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Security and privacy for IoT and fog computing paradigm
In the past decade, the revolution in miniaturization (microprocessors, batteries, cameras etc.) and manufacturing of new type of sensors resulted in a new regime of applications based on smart objects called IoT. Majority of such applications or services are to ease human life and/or to setup efficient processes in automated environments. However, this convenience is coming up with new challenges related to data security and human privacy. The objects in IoT are resource constrained devices and cannot implement a fool-proof security framework. These end devices work like eyes and ears to interact with the physical world and collect data for analytics to make expedient decisions. The storage and analysis of the collected data is done remotely using cloud computing. The transfer of data from IoT to the computing clouds can introduce privacy issues and network delays. Some applications need a real-time decision and cannot tolerate the delays and jitters in the network. Here, edge computing or fog computing plays its role to settle down the mentioned issues by providing cloud-like facilities near the end devices. In this paper, we discuss IoT, fog computing, the relationship between IoT and fog computing, their security issues and solutions by different researchers. We summarize attack surface related to each layer of this paradigm which will help to propose new security solutions to escalate it acceptability among end users. We also propose a risk-based trust management model for smart healthcare environment to cope with security and privacy-related issues in this highly un-predictable heterogeneous ecosystem.
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