What is it about?
Current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains
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Why is it important?
Digital technologies have changed the way supply chain operations are structured. By integrating AI/ML in the risk analytics, in this article we devise a new approach for cognitive data analytics, creating a stronger resilience of systems in their physical, digital and social dimensions. Our approach resolves around understanding how and when compromises happen, to enable systems to adapt and continue to operate safely and securely when they have been compromised. Cognition through AI/ML is the key topic of this research and cognitive real time intelligence would enable systems to recover and become more robust.
Perspectives
This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks.
Dr Petar Radanliev
University of Oxford
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This page is a summary of: Cyber risk at the edge: current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains, Cybersecurity, June 2020, Springer Science + Business Media,
DOI: 10.1186/s42400-020-00052-8.
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