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Epistemological Equation for Analysing Uncontrollable States in Complex Systems: Quantifying Cyber Risks from the Internet of Things

Author

Listed:
  • Petar Radanliev

    (University of Oxford)

  • David Roure

    (University of Oxford)

  • Pete Burnap

    (Cardiff University)

  • Omar Santos

    (Cisco Research Centre, Research Triangle Park)

Abstract

The Internet-of-Things (IoT) triggers data protection questions and new types of cyber risks. Cyber risk regulations for the IoT, however, are still in their infancy. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. At present, there are no self-assessment methods for quantifying IoT cyber risk posture. It is considered that IoT represent a complex system with too many uncontrollable risk states for quantitative risk assessment. To enable quantitative risk assessment of uncontrollable risk states in complex and coupled IoT systems, a new epistemological equation is designed and tested though comparative and empirical analysis. The comparative analysis is conducted on national digital strategies, followed by an empirical analysis of cyber risk assessment approaches. The results from the analysis present the current and a target state for IoT systems, followed by a transformation roadmap, describing how IoT systems can achieve the target state with a new epistemological analysis model. The new epistemological analysis approach enables the assessment of uncontrollable risk states in complex IoT systems—which begin to resemble artificial intelligence—and can be used for a quantitative self-assessment of IoT cyber risk posture.

Suggested Citation

  • Petar Radanliev & David Roure & Pete Burnap & Omar Santos, 2021. "Epistemological Equation for Analysing Uncontrollable States in Complex Systems: Quantifying Cyber Risks from the Internet of Things," The Review of Socionetwork Strategies, Springer, vol. 15(2), pages 381-411, November.
    • Handle: RePEc:spr:trosos:v:15:y:2021:i:2:d:10.1007_s12626-021-00086-5
    DOI: 10.1007/s12626-021-00086-5
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    References listed on IDEAS

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    1. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    2. Kim, Junmo, 2018. "Are countries ready for the new meso revolution? Testing the waters for new industrial change in Korea," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 34-39.
    3. Radanliev, Petar & De Roure, David & Nicolescu, Razvan & Huth, Michael & Mantilla Montalvo, Rafael & Cannady, Stacy & Burnap, Peter, 2018. "Future developments in cyber risk assessment for the internet of things," MPRA Paper 92567, University Library of Munich, Germany, revised Sep 2018.
    4. Christopher Whyte, 2018. "Crossing the Digital Divide: Monism, Dualism and the Reason Collective Action is Critical for Cyber Theory Production," Politics and Governance, Cogitatio Press, vol. 6(2), pages 73-82.
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    Cited by:

    1. Ramraj Dangi & Akshay Jadhav & Gaurav Choudhary & Nicola Dragoni & Manas Kumar Mishra & Praveen Lalwani, 2022. "ML-Based 5G Network Slicing Security: A Comprehensive Survey," Future Internet, MDPI, vol. 14(4), pages 1-28, April.
    2. Ammar Alazab & Ansam Khraisat & Moutaz Alazab & Sarabjot Singh, 2022. "Detection of Obfuscated Malicious JavaScript Code," Future Internet, MDPI, vol. 14(8), pages 1-15, July.
    3. Xiaoqian Zhu & Yinghui Wang & Jianping Li, 2022. "What drives reputational risk? Evidence from textual risk disclosures in financial statements," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.

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