IoT cyber risk: a holistic analysis of cyber risk assessment frameworks, risk vectors, and risk ranking process

• Published in: EURASIP Journal on Information Security 2020-05, Vol.2020 (1), p.1-18, Article 8
• Main Authors: Kandasamy, Kamalanathan, Srinivas, Sethuraman, Achuthan, Krishnashree, Rangan, Venkat P.
• Format: Article
• Language: English
• Subjects: Communications Engineering; Cybersecurity risk assessment frameworks; Engineering; Internet of Medical Things; Networks; Risk assessment; Risk rank; Risk vectors; Security Science and Technology; Signal,Image and Speech Processing; Systems and Data Security
• ISSN: 2510-523X; 2510-523X
• DOI: 10.1186/s13635-020-00111-0

Security vulnerabilities of the modern Internet of Things (IoT) systems are unique, mainly due to the complexity and heterogeneity of the technology and data. The risks born out of these IoT systems cannot easily fit into an existing risk framework. There are many cybersecurity risk assessment approaches and frameworks that are under deployment in many governmental and commercial organizations. Extending these existing frameworks to IoT systems alone will not address the new risks that have arisen in the IoT ecosystem. This study has included a review of existing popular cyber risk assessment methodologies and their suitability to IoT systems. National Institute of Standards and Technology, Operationally Critical Threat, Asset, and Vulnerability Evaluation, Threat Assessment & Remediation Analysis, and International Standards Organization are the four main frameworks critically analyzed in this research study. IoT risks are presented and reviewed in terms of the IoT risk category and impacted industries. IoT systems in financial technology and healthcare are dealt with in detail, given their high-risk exposure. Risk vectors for IoT and the Internet of Medical Things (IoMT) are discussed in this study. A unique risk ranking method to rank and quantify IoT risk is introduced in this study. This ranking method initiates a risk assessment approach exclusively for IoT systems by quantifying IoT risk vectors, leading to effective risk mitigation strategies and techniques. A unique computational approach to calculate the cyber risk for IoT systems with IoT-specific impact factors has been designed and explained in the context of IoMT systems.