Yazar "Aksoz, Ahmet" seçeneğine göre listele

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    Deep learning and explainable AI for email phishing classification: A comparative study of TabNet, NODE and FT-transformer models
    (Gazi Univ, 2025) Asal, Burcak; Oyucu, Saadin; Dogan, Ferdi; Polat, Onur; Aksoz, Ahmet
    In the changing landscape of cybersecurity threats, phishing emails indicate a persistent and damaging attack vector. This study investigates the effectiveness of deep learning models on a phishing email classification task using tabular data and focusing on TabNet, NODE (Neural Oblivious Decision Ensembles), and FT-Transformer architectures. The utilized dataset includes eight input features capturing linguistic and structural characteristics of emails, with a binary label indicating phishing or normal classification. Additionally, the NearMiss under-sampling approach is applied to address the significant class imbalance. Experimental results demonstrate that while all three models achieve strong performance, the FT-Transformer model outperforms TabNet and NODE by achieving the highest classification accuracy and balanced precision-recall scores. Additionally, explainable artificial intelligence (XAI) methods, SHAP and LIME, are employed to interpret the FT-Transformer model's decision-making process, which highlights the critical role of spelling errors, unique word counts, and urgency-related keywords in phishing detection. The findings emphasize the potential of transformer-based approaches for tabular cybersecurity applications and indicate the importance of interpretable AI in enhancing trust and transparency in phishing detection systems.
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    Electrification in Maritime Vessels: Reviewing Storage Solutions and Long-Term Energy Management
    (MDPI, 2025) Aksoz, Ahmet; Asal, Burcak; Golestan, Saeed; Gencturk, Merve; Oyucu, Saadin; Bicer, Emre
    Electric and hybrid marine vessels are marking a new phase of eco-friendly maritime transport, combining electricity and traditional propulsion to boost efficiency and reduce emissions. The industry's advancements in charging infrastructure and strict regulations help these vessels lead the way toward a sustainable and economically viable future in shipping. In this review, electric and hybrid marine vessels are discussed, including past applications and trend demonstrations. This paper systematically analyzes maritime vessels' energy management and battery systems, highlighting advances in lithium-based and alternative battery technologies. Additionally, the review examines the impact of these technologies on sustainability and operational efficiency in the maritime industry. This paper contributes to the field by presenting a holistic view of the challenges and solutions associated with the electrification of maritime vessels, aiming to inform future developments and policymaking in this dynamic sector. Unlike many existing reviews that focus exclusively on battery chemistries or energy management algorithms, this manuscript integrates multiple aspects of maritime electrification-including propulsion types, charging infrastructure, grid systems (MVDC), EMS, BMS, and AI applications-into one cohesive systems-level review. This cross-sectional integration is particularly rare in the literature and enhances the practical value of the review for designers, policymakers, and shipbuilders.