TITLE
METRICS-DRIVEN CYBER-RESILIENCE EVALUATION FOR RENEWABLE ENERGY INFRASTRUCTURES
AUTHOR(S)
Evgeni Hristov, Plamen Nakov
ABSTRACT
This paper presents an overview of quantitative and qualitative approaches to assessing the cyber resilience of distributed energy resource (DER) systems, focusing on the integration of KPI indicators, adaptive AI metrics and international security frameworks. A comprehensive resilience analysis model is proposed that combines three assessment levels: technical, organizational and adaptive. In the technical aspect, classic KPIs such as MTTD, MTTR, Detection Rate and Crypto Coverage are used, which measure the speed of detection and response to
incidents. The organizational level includes indicators for readiness and recovery, while the adaptive level introduces AI-based indices such as Cyber Resilience Index (CRI), Mean Time to Adapt (MTTA) and Reinforcement Learning Adaptation Efficiency (RAE). These metrics allow for a dynamic comparison of the level of protection and the effectiveness of response to cyber incidents in microgrids, hybrid RES systems and digitally connected DER infrastructures. The proposed methodology supports the transition from reactive to proactive cyber resilience by connecting measurable technical data with artificial intelligence for predictive assessment and adaptive security optimization.
DOI
How to cite this article:
Evgeni Hristov, Plamen Nakov, METRICS-DRIVEN CYBER-RESILIENCE EVALUATION FOR RENEWABLE ENERGY INFRASTRUCTURES, UNITECH – SELECTED PAPERS - 2025