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Responsible Resilience in Cyber–Physical–Social Systems: A New Paradigm for Emergent Cyber Risk Modeling

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  • Theresa Sobb

    (School of Systems and Computing, University of New South Wales, Canberra, ACT 2612, Australia)

  • Nour Moustafa

    (School of Systems and Computing, University of New South Wales, Canberra, ACT 2612, Australia)

  • Benjamin Turnbull

    (School of Systems and Computing, University of New South Wales, Canberra, ACT 2612, Australia)

Abstract

As cyber systems increasingly converge with physical infrastructure and social processes, they give rise to Complex Cyber–Physical–Social Systems (C-CPSS), whose emergent behaviors pose unique risks to security and mission assurance. Traditional cyber–physical system models often fail to address the unpredictability arising from human and organizational dynamics, leaving critical gaps in how cyber risks are assessed and managed across interconnected domains. The challenge lies in building resilient systems that not only resist disruption, but also absorb, recover, and adapt—especially in the face of complex, nonlinear, and often unintentionally emergent threats. This paper introduces the concept of ‘responsible resilience’, defined as the capacity of systems to adapt to cyber risks using trustworthy, transparent agent-based models that operate within socio-technical contexts. We identify a fundamental research gap in the treatment of social complexity and emergence in existing the cyber–physical system literature. To address this, we propose the E3R modeling paradigm—a novel framework for conceptualizing Emergent, Risk-Relevant Resilience in C-CPSS. This paradigm synthesizes human-in-the-loop diagrams, agent-based Artificial Intelligence simulations, and ontology-driven representations to model the interdependencies and feedback loops driving unpredictable cyber risk propagation more effectively. Compared to conventional cyber–physical system models, E3R accounts for adaptive risks across social, cyber, and physical layers, enabling a more accurate and ethically grounded foundation for cyber defence and mission assurance. Our analysis of the literature review reveals the underrepresentation of socio-emergent risk modeling in the literature, and our results indicate that existing models—especially those in industrial and healthcare applications of cyber–physical systems—lack the generalizability and robustness necessary for complex, cross-domain environments. The E3R framework thus marks a significant step forward in understanding and mitigating emergent threats in future digital ecosystems.

Suggested Citation

  • Theresa Sobb & Nour Moustafa & Benjamin Turnbull, 2025. "Responsible Resilience in Cyber–Physical–Social Systems: A New Paradigm for Emergent Cyber Risk Modeling," Future Internet, MDPI, vol. 17(7), pages 1-24, June.
  • Handle: RePEc:gam:jftint:v:17:y:2025:i:7:p:282-:d:1687392
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    References listed on IDEAS

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    1. Saeed, Umer & Jan, Sana Ullah & Lee, Young-Doo & Koo, Insoo, 2021. "Fault diagnosis based on extremely randomized trees in wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
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    3. Basim Mahbooba & Mohan Timilsina & Radhya Sahal & Martin Serrano & Ahmed Mostafa Khalil, 2021. "Explainable Artificial Intelligence (XAI) to Enhance Trust Management in Intrusion Detection Systems Using Decision Tree Model," Complexity, Hindawi, vol. 2021, pages 1-11, January.
    4. Carolina Pereira & Anabela Marto & Roberto Ribeiro & Alexandrino Gonçalves & Nuno Rodrigues & Carlos Rabadão & Rogério Luís de Carvalho Costa & Leonel Santos, 2025. "Security and Privacy in Physical–Digital Environments: Trends and Opportunities," Future Internet, MDPI, vol. 17(2), pages 1-23, February.
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