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  • Photo du rédacteurHélène Dufour

A Robust Statistical Framework for Cyber-Vulnerability Prioritisation Under Partial Information

Proactive cyber-risk assessment is gaining importance due to its potential benefits in preventing cyber incidents across various sectors and addressing emerging vulnerabilities in cyber-physical systems. This study presents a robust statistical framework, using mid-quantile regression, to assess cyber vulnerabilities, rank them, and measure accuracy while dealing with partial knowledge. The model is tested with simulated and real data to support informed decision-making in operational scenarios.


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Comments on the Final Trilogue Version of the AI Act

“This paper provides a comprehensive analysis of the recent EU AI Act, the regulatory framework surrounding Artificial Intelligence (AI), focusing on foundation models, open-source exemptions, remote

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