动态IoT-Edge资源扩散中渗透计算范式的机会主义安全架构

Likhwa Mlotshwa, Sheunesu M. Makura, Nickson M. Karie, V. Kebande
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引用次数: 2

摘要

由于边缘计算的存在,物理资源异质性的增加对物联网(IoT)产生了积极和消极的影响。因此,需要对物联网、云和边缘资源进行有效的动态管理,以解决资源迁移过程中存在的低级约束。然而,物联网设备和数据的爆炸式增长使得微服务的编排能够采用机会主义的方法来部署应用程序和服务在物联网平台的边缘。一种值得注意的方法是渗透计算,它允许联邦云中的资源能够从溶质(网络属性和实体)浓度较高的生态系统扩散到溶质(应用程序、分层接口和服务)。我们认为,虽然计算资源和应用程序能够从联邦环境移动到云部署模型,到边缘,然后到物联网生态系统,但由于动态紧急配置,威胁和攻击的易感机会更高,这些威胁和攻击可能直接针对新兴的边缘应用程序/数据。本文提出了一个5层机会主义架构,它在渗透计算范式的不同级别上增加了安全度量。提议的5层安全架构解决了自主保护资源的需求-边缘计算,边缘存储和新兴边缘配置,因为计算资源在跨物联网设备的异构边缘和云数据中心中移动到更高的溶质。这是通过提出安全度量来实现的,这些度量以一定程度的确定性解决了当前的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Opportunistic security architecture for osmotic computing paradigm in dynamic IoT-Edge's resource diffusion
Increased heterogeneity of physical resources has had positive and negative effects in Internet of Things (IoT) through the existence of edge computing. As a result, there has been a need for effective dynamic management of IoT, cloud and edge resources, in order to address the existence of low-level constraints during resource migration. Nevertheless, the explosion of IoT devices and data has allowed orchestration of microservices to adopt an opportunistic approach to how applications and services are deployed in the edge in IoT platform. A notable approach has been osmotic computing that allows resources from a federated cloud to be able to diffuse from an ecosystem of higher solute (network properties and entities) concentration to solvent (applications, layered interfaces and services). We posit that, while computing resources and applications are able to move from the federated environment, to the cloud deployable models, to the edge, then to IoT ecosystem, there is a higher chance of susceptibility of threats and attacks that may be directed to the emerging edge applications/data due to dynamic emergent configurations. This paper proposes a 5-layer opportunistic architecture that adds security metrics across different levels of osmotic computing paradigm. The proposed 5-layer security architecture addresses the need for autonomously securing resources-edge computation, edge storage and emerging edge configurations as the computing resources move to a higher solute in heterogenous edge and cloud datacenters across IoT devices. This has been achieved by proposing security metrics that address the prevailing challenge with a degree of certainty.
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