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Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge

Author

Listed:
  • Petar Radanliev

    (University of Oxford)

  • David Roure

    (University of Oxford)

  • Max Kleek

    (University of Oxford)

  • Uchenna Ani

    (University College London)

  • Pete Burnap

    (Cardiff University)

  • Eirini Anthi

    (Cardiff University)

  • Jason R. C. Nurse

    (University of Kent)

  • Omar Santos

    (Cisco Research Centre)

  • Rafael Mantilla Montalvo

    (Cisco Research Centre)

  • La’Treall Maddox

    (Cisco Research Centre)

Abstract

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

Suggested Citation

  • Petar Radanliev & David Roure & Max Kleek & Uchenna Ani & Pete Burnap & Eirini Anthi & Jason R. C. Nurse & Omar Santos & Rafael Mantilla Montalvo & La’Treall Maddox, 2021. "Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge," Environment Systems and Decisions, Springer, vol. 41(2), pages 236-247, June.
    • Handle: RePEc:spr:envsyd:v:41:y:2021:i:2:d:10.1007_s10669-020-09792-x
    DOI: 10.1007/s10669-020-09792-x
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    References listed on IDEAS

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    Cited by:

    1. Zachary A. Collier & James H. Lambert & Igor Linkov, 2021. "Algorithms and models for decision making in advanced technology systems," Environment Systems and Decisions, Springer, vol. 41(2), pages 179-180, June.

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