A Secure Data Ecosystem Testbed
The Edge-Cloud Continuum (ECC) has emerged as a key enabler for the next generation of data-driven AI applications to effectively address challenges related to latency, bandwidth and regulatory compliance. Nonetheless, securing ECC environments remains a challenge, as traditional perimeter based security measures are inadequate for the inherently distributed and borderless nature of ECC, where data processing occurs across multiple devices and domains. The Zero Trust (ZT) security paradigm emerges to address these critical security challenges by emphasising stringent access controls, continuous authentication and least privileged access policies to minimise attack surfaces and mitigate potential cyber threats. Despite its relevance, there is a notable lack of ZT-enabled testing environments that allow researchers and developers to evaluate ECC applications under realistic security and regulatory constraints. This paper presents a ZT-enabled testbed (ECC Testbed) that enables evaluation of data-driven applications within authentic security and regulatory contexts. The ECC testbed is engineered to support the practical deployment of secure, efficient and regulation-aware edge-cloud solutions. It also streamlines the onboarding process for new application deployments. By filling the current gap in testing environments for ECC applications, ECC testbed serves as a valuable resource for researchers and developers. Through the integration of robust security measures, it supports and promotes the safe adoption of ECC solutions in real-world scenarios.
Authors
- Sourabh Bharti (ORCID: https://orcid.org/0000-0002-3135-6339)
- Tharindu Ranathunga (ORCID: https://orcid.org/0009-0001-8914-7708)
- Alan McGibney (ORCID: https://orcid.org/0000-0002-0665-2005)
- Susan Rea (ORCID: https://orcid.org/0000-0002-4388-661X)
- Indika Dhanapala (ORCID: https://orcid.org/0000-0003-4091-4870)
Institutions
- Munster Technological University (IE)
Publication Details
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1109/smartcomp65954.2025.00090
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00