Security Analysis of Fleet Management Systems

• Mariam Ibrahim,
• Ruba Elhafiz,

Vol. 19, No. 11, November 30, 2025
10.3837/tiis.2025.11.017, Download Paper (Free):

• Attack Graph
• Cyber-Physical Systems
• Fleet management system
• Soft Actor-Critic
• Sustainable cities and communities

Abstract

Fleet Management (FM) automation relies on preprogrammed systems to perform various functions continuously, minimizing human interaction and resulting in predictable actions that are vulnerable to manipulation. Integrating the Internet of Things (IoT) into the Fleet Management System (FMS) heightens its susceptibility to cyberattacks, which can be difficult to detect and comprehend. This paper highlights the security vulnerabilities within the FMS and presents a strategy for utilizing and visualizing its attack graph. A model-checker, JKind, is employed to continuously verify a security condition, while the system is formally modeled using the Architecture Analysis and Design Language (AADL). The generated attack graph provides a comprehensive view of potential attack paths and vulnerabilities. Additionally, the Soft Actor-Critic (SAC) algorithm is applied to identify the optimal attack paths within the graph, ensuring that the most harmful sequences are prioritized. Effective visualization and analysis of attack paths are crucial for enhancing the security posture of fleet management operations. Furthermore, the attack graph helps suggest the optimal strategic deployment of Intrusion Detection Systems (IDS) with minimal resources. This targeted approach ensures efficient protection of the FMS, maximizing security coverage while minimizing costs.

Statistics

Cite this article