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Swarm Intelligence Based Multi-Agent Communication Model for Securing Healthcare Ecosystem

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conference contribution
posted on 2023-09-01, 15:17 authored by Patrizia Ribino, Shareeful Islam, Mario Ciampi, Spyros Papastergiou
The healthcare ecosystem is complex by its inherent nature, which consists of a heterogeneous set of actors, entities, and sub-systems to deliver multidisciplinary and collaborative health services. The increased use of connected medical devices makes such an ecosystem more vulnerable and increases the cyber-attack surface. Traditional security methods are insufficient to deal with such a high degree of interconnected medical and IoT devices. There is a need for security approaches based on concepts of collaboration, cooperation, autonomy and dynamism to ensure timely security of the whole healthcare ecosystem. This work adopts swarm-based principles with multi-agent systems to meet collaboration, distribution and robustness requirements, thus improving the healthcare ecosystem’s security. The paper presents a swarm-based agent-to-agent communication model founded on the collaboration among primary and supervisor agents to acquire new knowledge related to the healthcare ecosystem. The proposed model is based on the direct collaboration between primary agents that provides supervisor agents with local security-related information and the indirect collaboration between supervisor agents that exchange stigmergic information through the environment to make a collectively informed decision. The communication model is implemented using the BDI (Belief-Desire-Intention) approach. The preliminary results show the communication model’s robustness, scalability and responsiveness for securing the healthcare ecosystem.

History

Page range

50-61

ISSN

2367-3389

Publisher

Springer International Publishing

ISBN

9783031213328

Conference proceeding

Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022)

Name of event

International Conference on Ubiquitous Computing and Ambient Intelligence

File version

  • Accepted version

Language

  • eng

Legacy posted date

2023-03-02

Legacy creation date

2023-03-02

Legacy Faculty/School/Department

Faculty of Science & Engineering

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