Integrated Safety–Security Modelling in Digital Substations

Strategy Phasing of Cyber Attacks on Digital Substations

This paper proposes Substation Cyber Attack Strategy Phasing (SubCASP), a Hidden Markov Model(HMM)- based method that fuses IDS data logs to infer the current attack phase, next attack phase, and retrospective attack path.

A Digital Twin-based Approach Supporting the Calculation of Cyber-Attack Success Probability in Process Plants

Cyber-Physical Railway Security using Smart Port Operations

The interconnection of advanced signalling systems, logistics and operational networks involves IoT technologies in railway systems necessities advanced security measures to prevent cyber attacks to such systems which are used in the smart port infrastructures. This paper proposes a cyber-physical security framework mathematically and AI based for railway–smart port operations based on multi-layer security, intelligence intrusion detection system, and stability constrained monitoring models. The framework introduces network state evolution equations, communication delay modelling, secure logistics optimization, Lyapunov stability analysis and layered security convergence theorems to ensure secure network operation in the event of a cyber attack. Signalling manipulation, packet injection, spoofing and communication jamming attacks are detected using the AI based anomaly detection. Based on experimental analysis, it can be concluded that the proposed cyber-physical transportation security architecture is effective, robust, and reliable with intrusion detection accuracy of 97.2% and higher precision and recall, F1 score.

Development of Risk Assessment and Minimization Models for Cyber Incidents in Interconnected Automotive and Power Systems

The paper investigates the critical problem of ensuring cyber resilience within the integrated ecosystems of automotive transport and energy infrastructure, which are becoming increasingly interdependent due to the mass adoption of electric vehicles and Smart Grid technologies. The study provides a comprehensive analysis of the threat landscape, focusing on specific attack vectors targeting electric vehicle charging stations (EVCS) and the communication protocols of the Vehicle-to-Grid (V2G) interface. It is demonstrated that vulnerabilities in the ISO/IEC 15118 and OCPP protocols can be exploited to initiate cascading failures that transcend the boundaries of the transport network and impact the stability of the regional power grid. The central contribution of this research is the development of a formalized mathematical model for multi-layer risk assessment, which utilizes a probabilistic approach to quantify the impact of cyber-physical attacks on system availability and data integrity. Unlike existing one-dimensional models, the proposed methodology accounts for the interconnectedness of nodes, where a security breach in a single vehicle or charging point acts as a catalyst for large-scale energy imbalances. The paper details a systematic risk minimization framework that integrates proactive and reactive measures: from the deployment of specialized intrusion detection systems (IDS) optimized for industrial control protocols to the implementation of adaptive load management algorithms that mitigate the effects of malicious demand-side manipulation. Simulation results presented in the study confirm that the proposed model effectively identifies high-risk convergence points with a sensitivity improvement of 15-20% compared to traditional NIST-based frameworks. The research findings provide a theoretical and practical basis for government agencies and critical infrastructure operators to develop robust cybersecurity strategies in the era of total digitalization of transport and energy assets. The developed models contribute to the creation of autonomous defense mechanisms capable of maintaining operational continuity under adversarial conditions.

Integrating Graphical and Formal Modelling to Analyse the Impact of Cyberattacks on Safety of Networked Control Systems

Over recent years, the number of cyberattacks on safety-critical systems, including railways, has been rapidly increasing. To analyze the impact of cyberattacks on safety, we need to create methods supporting a systematic and rigorous analysis of system behavior in the presence of cyber threats. In this paper, we propose a novel methodology and automated tool support for an integrated analysis of the impact of cyberattacks on the safety of railway systems. Our approach relies on graphical modeling in SysML, HAZOP-based analysis of cyber threats, and formal modeling in Event-B. The proposed approach allows the designers to identify and visualize the safety requirements that become violated as a result of various cyberattacks.

A Review of Digital Oil Field Cybersecurity with a Perspective on Cyberphysical Attack Mitigation with the Integration of Physically Unclonable Functions

The System-on-Chip (SoC) strategies exemplifying the use of Physically Unclonable functions (PUF) in the generation of data provenance attributes to boost the cyber-physical security infrastructures in digital oil fields are highlighted.