Cybersecurity in Railways : Identifying and Communicating Risks using System Dynamics Modeling

Abstract: Extensive digitization is currently underway in the railway sector, which has resulted in several benefits and improvements, but also challenges. The increased use of digital technologies increases the risks of vulnerabilities and susceptibility to cyberattacks. The effects of a cyber attack can have significant consequences on operations such as financial losses and damaged reputations, or in the worst-case scenario, devastating consequences where the lives of passengers are endangered. With the ongoing digitalization of the railways and the growing concern for cybersecurity, stakeholders in the sector have identified the need to systematically understand the risks of digitization related to cybersecurity and safety. Therefore, this study aims to identify and communicate these risks using system dynamics modeling. This study evaluated how actors in the railway sector reason about risks in the railway, how safety and cybersecurity are related, and new risks associated with digitalization and cybersecurity that have not been mentioned in the literature before. A qualitative study was conducted to answer the research question. Ten actors from different parts of the railway value chain were interviewed, and secondary data was collected from articles and reports within the area of cybersecurity and the railways. The results revealed a connection between cybersecurity and safety which could be seen through the chain of consequences that can arise from a cyberattack and in the event of loss of data availability and integrity. Based on this, core elements of the system and the relationships between them could be identified, from which the causal loop diagram (CLD) was constructed. New risks that were identified were the safety culture that permeates the railway industry, unclear areas of responsibility that are a result of deregulation in the Swedish railway sector, and competitiveness. Insights from the system dynamic model identified a reinforcing loop telling a causal story that shows that low cybersecurity priorities could lead to decreased safety on the railway. This further demonstrates the usefulness of identifying and communicating risks using system dynamics modeling.