Incorporating FAIR into Bayesian Network for Numerical Assessment of Loss Event Frequencies of Smart Grid Cyber Threats

• DOI: 10.1007/s11036-018-1047-6
• Publication Date: 2018-09-01T05:29:40Z
• Authors: Anhtuan Le; Yue Chen; Kok Keong Chai; Alexandr Vasenev; Lorena Montoya
• Keywords: Robustness; Rank (graph theory)

In today's cyber world, assessing security threats before implementing smart grids is essential to identify and mitigate the risks. Loss Event Frequency (LEF) a concept provided by well-known Factor Analysis of Information Risk (FAIR) framework assess categorize into five classes, based on their severity. As number increasing, it possible that many might fall under same LEF category, but FAIR cannot provide any further mechanism rank them. this paper, we propose method incorporate FAIR's Bayesian Network (BN) derive numerical assessments threat The BN probabilistic relations are inferred from look-up tables reflect conserve appraisal. Our approach extends functionality providing more detailed ranking, allowing fuzzy inputs, enabling illustration input-output relations, identifying most influential element improve effectiveness countermeasure investment. Such improvements demonstrated applying in grid robustness research project (IRENE).