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    Öğe
    Enhanced Phishing Website Detection Through Effective Feature Selection With Time-Varying Mirrored S-Shaped Transfer Function
    (Wiley, 2025) Kilic, Fatih; Erdi, Kemal; Aktas, Muhammet
    The increasing use of websites and the increasing sophistication of cybercrimes have highlighted the need for effective prevention mechanisms. Phishing attacks represent a significant cybersecurity threat, as they exploit human weaknesses and deceptive web-based tactics to achieve unauthorized access to sensitive user information. Due to the evolving and increasingly sophisticated methodologies cybercriminals use, there is an urgent demand for advanced and innovative approaches to detect and mitigate these threats accurately. In this paper, a novel approach is proposed by incorporating a time-varying mirrored S-shaped transfer function into three prominent binary optimization algorithms: Binary Grey Wolf Optimization (TVBGWO), Binary Particle Swarm Optimization (TVBPSO), and Binary Harris Hawk Optimization (TVBHHO). The proposed models are rigorously evaluated using a publicly available phishing website dataset. Using a time-varying mirrored S-shaped transfer function for feature selection enables metaheuristic algorithms to improve the balance between exploration and exploitation, thus enhancing their ability to classify phishing websites accurately. The Friedman test confirms statistically significant differences among the compared methods (X-2 = 70.3, p = 8.87 x 10(-14)). The Wilcoxon Rank-Sum test is applied to determine the difference in the performance of the time-varying methods among the standard BGWO, BHHO, and BPSO algorithms in this study. TV-based variants of BPSO and BGWO showed a solid and balanced performance, achieving the highest test accuracy (90.3% and 90.2%) and F1-scores (0.91%). Proposed models achieve promising high accuracy and F1-score performance in detecting phishing websites using fewer features and suggesting their potential.
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    Öğe
    Phishing website detection based on a novel artificial intelligence technique
    (Adana Alparslan Türkeş Bilim ve Teknoloji Üniversitesi, 2023) Erdi, Kemal; Kılıç, Fatih
    İnternet kullanımının artması nedeniyle araştırmacılar siber suçların önlenmesine yönelik geniş çapta çalışmalar yapmaktadır. Siber suçlardan biri de oltalama web siteleridir. Siber suçlular giderek daha karmaşık taktikler uyguladıkça, bu tehditleri tespit etmek ve önlemek için yenilikçi yaklaşımlara olan ihtiyaç da artıyor. Bu tezde BGWO, BPSO ve BHHO için zamanla değişen aynalı S-şekilli transfer fonksiyonu uygulanmış ve önerilen modeller oltalama web sitesi veri seti üzerinde test edilmiştir. Önerilen modeller, oltalama web sitesi veri kümesinde umut verici sonuçlara sahiptir