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REVIEW article

Front. Big Data
Sec. Cybersecurity and Privacy
Volume 7 - 2024 | doi: 10.3389/fdata.2024.1402745

AI Security and Cyber Risk in IoT Systems

Provisionally accepted
Petar Radanliev Petar Radanliev 1*David De Roure David De Roure 1Carsten Maple Carsten Maple 2Jason Nurse Jason Nurse 3Razvan Nicolescu Razvan Nicolescu 4Uchenn D. Ani Uchenn D. Ani 5
  • 1 University of Oxford, Oxford, United Kingdom
  • 2 University of Warwick, Coventry, West Midlands, United Kingdom
  • 3 University of Kent, Canterbury, Kent, United Kingdom
  • 4 University College London, London, England, United Kingdom
  • 5 Keele University, Keele, United Kingdom

The final, formatted version of the article will be published soon.

    Internet-of-Things (IoT) refers to low-memory connected devices used in various new technologies, including drones, autonomous machines, and robotics. The article aims to understand better cyber risks in low-memory devices and the challenges in IoT risk management. The article includes a critical reflection on current risk methods and their level of appropriateness for IoT. We present a dependency model tailored in context towards current challenges in data strategies and make recommendations for the cybersecurity community. The model can be used for cyber risk estimation and assessment and generic risk impact assessment. The model is developed for cyber risk insurance for new technologies (e.g., drones, robots). Still, practitioners can apply it to estimate and assess cyber risks in organisations and enterprises. Furthermore, this paper critically discusses why risk assessment and management are crucial in this domain and what open questions on IoT risk assessment and risk management remain areas for further research. The paper then presents a more holistic understanding of cyber risks in the IoT. We explain how the industry can use new risk assessment, and management approaches to deal with the challenges posed by emerging IoT cyber risks. We explain how these approaches influence policy on cyber risk and data strategy. We also present a new approach for cyber risk assessment that incorporates IoT risks through dependency modelling. The paper describes why this approach is well suited to estimate IoT risks.

    Keywords: artificial intelligence, Internet-of-Things (IoT), Cyber risk management, Cyber risk assessment, cyber risk estimation, Cyber risk insurance, Risk impact assessment, AI security

    Received: 25 Mar 2024; Accepted: 16 Sep 2024.

    Copyright: © 2024 Radanliev, De Roure, Maple, Nurse, Nicolescu and Ani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Petar Radanliev, University of Oxford, Oxford, United Kingdom

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.