Decentralised Identity Management solution for zero-trust multi-domain Computing Continuum frameworks

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2024-08-06 DOI:10.1016/j.future.2024.08.003
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Abstract

The adoption of the Computing Continuum is characterised by the seamless integration of diverse computing environments and devices. In this dynamic landscape, sharing resources across the continuum is becoming a reality and security must move an step forward, specially in terms of authentication and authorisation for such a distributed and heterogeneous environments. The need for robust identity management is paramount and, in this regard, Decentralised Identity Management (DIM) emerges as a promising solution. It leverages decentralised technologies to secure and facilitate identity interactions across the Computing Continuum. Particularly, to enhance security and privacy, it would be desirable to apply the principles of Self-Sovereign Identity (SSI). In this paradigm, users have full ownership and control of their digital identities that empowers individuals to manage and share their identity data on a need-to-know basis. These mechanisms could contribute to improve security properties during continuum resource management operations. In this context, this paper presents the design, workflows and implementation of a solution that provides authentication/authorisation features to distributed zero-trust based infrastructures across the continuum, enhancing security in resource sharing and resource acquisition stages. To this aim, the solution relies on key aspects like decentralisation, interoperability, trust management and privacy-enhancing capabilities. The decentralisation leverages distributed ledger technologies, such as blockchain, to establish a decentralised identity ecosystem. The solution prioritises interoperability, enabling nodes to seamlessly access and share their identities across different domains and environments. Trustworthiness is at the core of DIM, and privacy is also considered, incorporating privacy-preserving techniques that individuals to selectively disclose identity attributes while safeguarding sensitive information. The implementation includes different operations for allowing continuum frameworks to be enhanced with decentralised authentication and authorisation features. The performance has been evaluated measuring the impact for the adoption of the solution. The most expensive task, the self-identity generation, takes only a few seconds (in our deployment) and it is only executed once. Authorisation tasks operate in the millisecond range, which is a totally invaluable time if incorporated into resource acquisition processes in frameworks such as Liqo, used in the scope of FLUIDOS project.

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零信任多域计算的分散式身份管理解决方案 Continuum 框架
计算连续性的特点是各种计算环境和设备的无缝集成。在这一动态环境中,跨连续体共享资源正在成为现实,安全问题必须向前迈进一步,特别是在这种分布式异构环境的身份验证和授权方面。在这方面,分散式身份管理(DIM)是一个很有前途的解决方案。它利用去中心化技术来确保和促进整个计算过程中的身份互动。特别是,为了提高安全性和隐私性,最好采用自主身份(SSI)原则。在这种模式下,用户对自己的数字身份拥有完全的所有权和控制权,从而使个人有能力在 "需要知道 "的基础上管理和共享自己的身份数据。这些机制有助于提高连续资源管理操作过程中的安全性能。在此背景下,本文介绍了一种解决方案的设计、工作流程和实施,该解决方案可为整个连续体中基于零信任的分布式基础设施提供身份验证/授权功能,从而增强资源共享和资源获取阶段的安全性。为此,该解决方案依赖于去中心化、互操作性、信任管理和隐私增强功能等关键方面。去中心化利用区块链等分布式账本技术,建立一个去中心化的身份生态系统。该解决方案优先考虑互操作性,使节点能够在不同领域和环境中无缝访问和共享其身份。可信性是 DIM 的核心,同时也考虑到了隐私问题,采用了隐私保护技术,让个人在保护敏感信息的同时有选择地披露身份属性。实施过程包括不同的操作,允许连续框架通过分散认证和授权功能得到增强。对性能进行了评估,衡量采用该解决方案的影响。最昂贵的任务--自我身份生成--只需要几秒钟(在我们的部署中),而且只执行一次。授权任务的运行时间仅为几毫秒,如果将其纳入 FLUIDOS 项目所使用的 Liqo 等框架的资源获取流程中,这将是一个非常宝贵的时间。
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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