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Digital technologies have changed the way supply chain operations arestructured. In this article, we conduct systematic syntheses of literature onthe impact of new technologies on supply chains and the related cyber risks. Ataxonomic/cladistic approach is used for the evaluations of progress in thearea of supply chain integration in the Industrial Internet of Things andIndustry 4.0, with a specific focus on the mitigation of cyber risks. Ananalytical framework is presented, based on a critical assessment with respectto issues related to new types of cyber risk and the integration of supplychains with new technologies. This paper identifies a dynamic and self-adaptingsupply chain system supported with Artificial Intelligence and Machine Learning(AI/ML) and real-time intelligence for predictive cyber risk analytics. Thesystem is integrated into a cognition engine that enables predictive cyber riskanalytics with real-time intelligence from IoT networks at the edge. Thisenhances capacities and assist in the creation of a comprehensive understandingof the opportunities and threats that arise when edge computing nodes aredeployed, and when AI/ML technologies are migrated to the periphery of IoTnetworks.

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