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  

作　　者：Petar Radanliev David De Roure Kevin Page Jason R.C.Nurse Rafael Mantilla Montalvo Omar Santos La’Treall Maddox Pete Burnap 

机构地区：[1]Oxford e-Research Centre,Engineering Sciences Department,University of Oxford,Oxford,England [2]School of Computing,University of Kent,Kent,England,UK [3]Cisco Research Centre,Research Triangle Park,Durham,North Carolina,USA [4]School of Computer Science and Informatics,Cardiff University,Cardiff,Wales,UK.

出　　处：《Cybersecurity》2020年第1期155-175,共21页网络空间安全科学与技术（英文）

基　　金：This work was funded by the UK EPSRC[grant number:EP/S035362/1,EP/N023013/1,EP/N02334X/1]and by the Cisco Research Centre[grant number 1525381].

摘　　要：Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.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.

关 键 词：Industry 4.0 Supply chain design Transformational design roadmap IIoT supply chain model Decision support for information management artificial intelligence and machine learning(AI/ML) dynamic self-adapting system cognition engine predictive cyber risk analytics 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP309[自动化与计算机技术—控制科学与工程]