ICCA: An Improved Intrusion Detection Algorithm for Healthcare Data Classification and URLs phishing

Basit Öğe Kaydı
dc.contributor.authorAlarbi, Abdalraouf
dc.contributor.authorAlbayrak, Zafer
dc.contributor.authorÇakmak, Muhammet
dc.contributor.authorAltunay, Hakan Can
dc.date.accessioned2026-04-25T14:13:30Z
dc.date.available2026-04-25T14:13:30Z
dc.date.issued2026
dc.departmentSinop Üniversitesi
dc.description.abstractClassification is a fundamental task in machine learning that involves assigning data instances to one or more predefined categories or classes. Among the various classification algorithms available is the Core Classification Algorithm (CCA). However, CCA has limitations, particularly when dealing with high-dimensional data, which can negatively affect its classification performance. To address these limitations, this study proposes a new algorithm called the Improved Core Classification Algorithm (ICCA), which enhances the performance of CCA by incorporating novel features and techniques. In this article, the principles and design of ICCA were described and its performance was compared to that of CCA and other state-of-the-art classification methods on four datasets from the healthcare and phishing URLs domains. Experimental results on four datasets demonstrate that ICCA consistently outperforms the original CCA, achieves the highest accuracy on the high-dimensional phishing and cardiovascular datasets, and remains competitive on imbalanced medical data. Overall, this work contributes to the advancement of classification algorithms and provides a valuable tool for various real-world applications. © 2026, Budapest Tech Polytechnical Institution. All rights reserved.
dc.identifier.endpage181
dc.identifier.issn1785-8860
dc.identifier.issue5
dc.identifier.scopus2-s2.0-105035302721
dc.identifier.scopusqualityQ1
dc.identifier.startpage165
dc.identifier.urihttps://hdl.handle.net/11486/8118
dc.identifier.volume23
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherBudapest Tech Polytechnical Institution
dc.relation.ispartofActa Polytechnica Hungarica
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260420
dc.subjectClassification
dc.subjectcybersecurity
dc.subjectHybridization
dc.subjectPhising attacks
dc.titleICCA: An Improved Intrusion Detection Algorithm for Healthcare Data Classification and URLs phishing
dc.typeArticle

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu