Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Browsing Scopus İndeksli Yayınlar Koleksiyonu by Institution Author "Bozdal, Mehmet"

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    Cyber Threats to Green Hydrogen Production Within a Solar Microgrid
    (Springer International Publishing AG, 2025) Bozdal, Mehmet; Pourmirza, Zoya
    The transition towards sustainable energy systems depends heavily on the reliable operation of renewable energy infrastructure, which is increasingly interconnected and digitized. Therefore, ensuring cybersecurity resilience is essential for maintaining the reliability and safety of renewable energy systems in a rapidly evolving digital landscape. This paper investigates the economic implications of data integrity and system configuration attacks on a green hydrogen production system within a solar microgrid. Through a comprehensive analysis, the vulnerability of the system to cyber intrusions that manipulate relay settings, electricity prices, and hydrogen level, is examined. Drawing on a multidisciplinary framework encompassing energy economics, cybersecurity, and renewable energy technologies, a methodological approach is developed to quantify the direct economic impacts of attacks. Simulation results indicate that such attacks can decrease profits by up to 14%.
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    Security Through Digital Twin-Based Intrusion Detection: A SwaT Dataset Analysis
    (Institute of Electrical and Electronics Engineers Inc., 2023) Bozdal, Mehmet
    Digital twin, as a virtual replica of physical entity, offer valuable insights into Industrial Control System (ICS) behavior and characteristics. Leveraging the convergence of digital twins and cybersecurity, this research explores its role in securing critical infrastructure, using the Secure Water Treatment (SWaT) system as a case study. Existing intrusion detection systems (IDS) for SWaT encounter challenges related to requiring huge amounts of a dataset for training, being unable to adopt high data dimensionality, and adaptability to emerging threats. To address these issues, a hybrid digital twin model is proposed, combining physics-based models and data-driven approaches. This model facilitates precise attack localization and explainable IDS outcomes. The method exhibits promising capabilities for enhancing critical infrastructure security and adapting to evolving cyber threats. Experimental results demonstrate the ability to detect eight out of nine attack types. © 2024 Elsevier B.V., All rights reserved.
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    Temporal Logic-Based Intrusion Detection for Securing Connected Vehicles
    (Springer International Publishing AG, 2024) Bozdal, Mehmet
    Ensuring the security and integrity of in-vehicle communication networks (IVCNs) is paramount. The increasing connectivity of vehicles exposes them to unprecedented security vulnerabilities, necessitating innovative methodologies to safeguard against cyberattacks and unauthorized access. This research presents a novel approach to enhance IVCN security through the deployment of a Signal Temporal Logic (STL)-based Intrusion Detection System (IDS). Considering the limited resources of Electronic Control Units (ECUs), this approach offers an adaptive and lightweight solution that addresses the unique challenges posed by the dynamic nature of vehicular networks. The proposed STL-based IDS effectively detects a broad spectrum of intrusions while maintaining acceptable overhead for resource-constrained ECUs, thanks to its distributed architecture. Comprehensive experimental evaluations demonstrate significant performance improvements in detecting Denial of Service (DoS) attacks, achieving the highest accuracy of 0.996 and recall of 1.000. The system also excels in detecting fuzzy attacks, with the highest accuracy of 0.996.