The Economics of Cyber-Attacks on the Energy Sector: Evidence from Major Incidents and Risk Quantification Models

Abstract

Over the years, the rapid pace of digitalization in the energy sector has improved the connection between the economic stability and the cyber security, however, the broader financial consequences of cyber-attacks remain inadequately understood. This study aims to analyze the economic impact of cyber threats in energy sector through major incidents since 2010, focusing on direct losses, operational disruption, cascading impact and the wider societal cost. The case studies of Colonial Pipeline, Norsk Hydro, and Halliburton are explored which showcase that economic severity relies less on the company size or the ransom demands, instead depends more on the fact whether operational technology (OT) is disrupted. The study further covers well known economic methods such as Gordon-Loeb model, Value-at-Risk, Extreme Value Theory, and game-theoretic optimization, by integrating the systematic and cross sector effect. The findings indicate that socially optimal cyber investment can exceed firm-level investment decision based merely on private costs and expected loss. Additionally, the study explores emerging risks from AI-based attacks, distributed energy resource and quantum computing, which may alter the cyber losses from rare catastrophic events towards more frequent combined incidents. Overall, this study combines the evidence from real world incidents with economic modeling to offer a practical way to recognize cyber economic risk in energy sector. It additionally provide a way for policy makers, regulators and energy operations to move beyond immediate financial cost of attack and consider wider operational, societal and cross sector consequences.