Machine learning and cyber risk analytics at the edge

“

- 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.

”