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Towards Context-Based Authorizations for Interactions in Hypermedia-Driven Agent Environments - The CASHMERE Framework

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Engineering Multi-Agent Systems (EMAS 2023)

Abstract

Agent-oriented software engineering has recently seen a sustained effort towards the definition of a new class of Multi-Agent System design, called Hypermedia MAS, which promotes an alignment between MAS engineering and the Web architecture to enable development of large, open, dynamic and long-lived interaction systems. A major challenge in these envisioned MAS environments is enabling agents to discover the resources whose affordances they require. Hypermedia MAS design principles push for discovery and use of resources by exploiting the link structure of web resources, but little focus has been placed thus far in ensuring authorized access to the resources of a large MAS environment. To address this, we propose a framework for context-based authorizations for access and discovery of resources in a Hypermedia MAS, inspired by work on Attributed-Based Access Control and RDF Stream Reasoning. We detail the design of the framework functionality and the proposed integration with current Hypermedia MAS platforms, highlighting advantages, challenges and current limitations of the approach.

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Notes

  1. 1.

    NextLabs ABAC solution for business-critical data control: https://www.nextlabs.com/products/technology/abac/.

  2. 2.

    Styra - authorization as a service at scale: https://www.styra.com/blog/dynamic-authorization-with-policy-based-access-management/.

  3. 3.

    https://www.w3.org/TR/vcard-rdf/.

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Acknowledgement

This work has been supported by funding under grant agreement PN-III-P1-1.1-PD-2021-0756 from the Romanian National Research, Development and Innovation Plan.

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Correspondence to Alexandru Sorici .

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Sorici, A., Florea, A.M. (2023). Towards Context-Based Authorizations for Interactions in Hypermedia-Driven Agent Environments - The CASHMERE Framework. In: Ciortea, A., Dastani, M., Luo, J. (eds) Engineering Multi-Agent Systems. EMAS 2023. Lecture Notes in Computer Science(), vol 14378. Springer, Cham. https://doi.org/10.1007/978-3-031-48539-8_13

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  • DOI: https://doi.org/10.1007/978-3-031-48539-8_13

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