Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - Scopus: 10Security and Privacy Challenges, Solutions, and Open Issues in Smart Metering: A Review(Institute of Electrical and Electronics Engineers Inc., 2021-09-15) Win, Lae Lae; Tonyali, SametThe traditional power grid becomes ‘smart’ when it is combined with the communication and information technology. Along with smart grid, the traditional meter is replaced with smart meter. Smart meters play an important role in energy consumption reporting and, thereby, billing. Besides smart meters, the smart grid communication network is composed of heterogeneous devices that are communicating through public networks. Therefore, smart metering communications are susceptible to cyber-attacks and privacy breaches which are still under debating. This paper gives a brief overview of smart grid, smart metering, and the communication networks. Then, the privacy and security requirements of the smart grid network are derived. The various kind of cyber-attacks are discussed, after that, the different schemes and approaches that have been proposed in previous papers are reviewed. Lastly, the open issues on security and privacy of smart grid metering communications are highlighted. © 2022 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 3Security Through Digital Twin-Based Intrusion Detection: A SwaT Dataset Analysis(Institute of Electrical and Electronics Engineers Inc., 2023-10-18) Bozdal, MehmetDigital 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.Conference Object Citation - Scopus: 3Enhancing Intrusion Detection in Electric Networks Using Physics-Informed Random Forest(Institute of Electrical and Electronics Engineers Inc., 2024-10-16) Bozdal, Mehmet; Savasci, AlperThe increasing complexity of electric power networks has heightened their vulnerability to cyber-attacks, challenging traditional Intrusion Detection Systems (IDS) that rely on manually crafted rules. This paper introduces a novel approach that integrates physics-informed features and feature selection into a Random Forest (RF) model to enhance IDS performance. By deriving features such as complex power and impedance from fundamental electrical principles and applying SelectKBest for optimal feature selection, our method not only improves detection accuracy but also enhances efficiency by using fewer than half the features. Specifically, the feature-enriched RF model utilizing 55 features achieves an accuracy of 0.9667 and an F1-score of 0.9664, compared to 0.9576 and 0.9570 for the baseline RF model. This approach demonstrates the effectiveness of advanced feature engineering and selection techniques for improving the security and reliability of power network monitoring systems. © 2024 Elsevier B.V., All rights reserved.Conference Object Cyber Threats to Green Hydrogen Production Within a Solar Microgrid(Springer International Publishing AG, 2025) Bozdal, Mehmet; Pourmirza, ZoyaThe 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%.