Szczegóły Szczegóły PDF BIBTEX RIS Tytuł artykułu Ensemble learning approach to enhancing binary classification in Intrusion Detection System for Internet of Things Tytuł czasopisma International Journal of Electronics and Telecommunications Rocznik 2024 Wolumin vol. 70 Numer No 2 Afiliacje Soni : Faculty of Computer Sciences, Universitas Muhammadiyah Riau, Pekanbaru, Riau Indonesia and Faculty of Data Science and Computing, Universiti Malaysia Kelantan, City Campus, Pengkalan Chepa, 16100 Kota Bharu, Kelantan, Malaysia ; Remli, Muhammad Akmal : Faculty of Data Science and Computing, Universiti Malaysia Kelantan and Institute for Artificial Intelligence and Big Data, Universiti Malaysia Kelantan, City Campus, Pengkalan Chepa, 16100 Kota Bharu, Kelantan, Malaysia ; Mohd Daud, Kauthar : Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi Selangor, Malaysia ; Amien, Januar Al : Universitas Muhammadiyah Riau, Pekanbaru, Riau Indonesia and Faculty of Data Science and Computing, Universiti Malaysia Kelantan, City Campus, Pengkalan Chepa, 16100 Kota Bharu, Kelantan, Malaysia Autorzy Soni ; Remli, Muhammad Akmal ; Mohd Daud, Kauthar ; Amien, Januar Al Słowa kluczowe Binary classification ; XGBoost ; ToN IoT dataset ; ensemble technique Wydział PAN Nauki Techniczne Zakres 465-472 Wydawca Polish Academy of Sciences Committee of Electronics and Telecommunications Data 25.06.2024 Typ Article Identyfikator DOI: 10.24425/ijet.2024.149567 ; ISSN 2081-8491, eISSN 2300-1933