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Why is it important?

CPSs and IoT produce a vast amount of data, and the analysis of such big data requires advanced analytical tools. For clearing up the noise and inconsistency of the data, we almost certainly require AI-enhanced analytical tools.


- A new framework details a working prototype of AI-enabled dynamic cyber risk analytics at the edge. - The main findings from this paper include: 1. AI integration in communications networks and connected technology must evolve in an ethical manner that humans can understand, while maintaining maximum trust and privacy of the users; 2. The co-ordination of AI in CPS’s must be reliable to prevent abuse from insider threats, organised crime, terror organisations or state-sponsored aggressors; 3. Data risk is encouraging the private sector to take steps to improve the management of confidential and proprietary information intellectual property and to protect personally identifiable information; 4. Analysis of a dynamic and self-adopting AI design for a cognition engine mechanism for the control, analysis, distribution and management of probabilistic data.

Dr Petar Radanliev
University of Oxford

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This page is a summary of: Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge, SN Applied Sciences, October 2020, Springer Science + Business Media,
DOI: 10.1007/s42452-020-03559-4.
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