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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal TIMES CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi JurTI (JURNAL TEKNOLOGI INFORMASI) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Query : Jurnal Sistem Informasi METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi JURIKOM (Jurnal Riset Komputer) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jambura Journal of Electrical and Electronics Engineering JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA JPM: JURNAL PENGABDIAN MASYARAKAT International Journal of Engineering, Science and Information Technology Yayasan Cita Cendikiawan Al Khwarizmi Djtechno: Jurnal Teknologi Informasi JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen INCODING: Journal of Informatics and Computer Science Engineering EXPLORER Prosiding Snastikom Jurnal ABDIMAS Budi Darma Journal of Practical Computer Science (JPCS) Jurnal Informatika Teknologi dan Sains (Jinteks) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat Jurnal Indonesia Sosial Teknologi Jurnal Ilmu Komputer dan Sistem Informasi CompTech : Jurnal Ilmu Komputer dan Teknologi
Rahman, Sayuti
Universitas Medan Area, Medan, Indonesia
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Journal : Jurnal TIMES

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IMPROVING CYBERSECURITY TRAFFIC ANALYSIS VIA ENHANCED K-MEANS CLUSTERING WITH TRIANGLE INEQUALITY-BASED INITIALIZATION Hartono, Hartono; Khahfi Zuhanda, Muhammad; Rahman, Sayuti
Jurnal TIMES Vol 14 No 1 (2025): Jurnal TIMES
Publisher : STMIK TIME

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51351/jtm.14.1.2025823

Abstract

Clustering algorithms are essential in data mining and pattern recognition for grouping unlabeled data into meaningful clusters based on similarities. Among them, K-Means is widely used due to its simplicity and efficiency but suffers from sensitivity to initial centroid selection and inability to capture feature dependencies. This study proposes an Enhanced Mutual Information-based K-Means (MIK-Means) algorithm combined with Triangle Inequality and Lower Bound (TILB) seeding to improve clustering accuracy and computational efficiency, particularly in the context of network traffic classification for cybersecurity applications. The TILB method accelerates the initialization phase by reducing redundant distance calculations using mathematical pruning techniques, thereby selecting well-distributed initial centroids efficiently. Meanwhile, MIK-Means incorporates mutual information as a similarity measure during clustering assignment, enabling the algorithm to capture complex statistical dependencies among features, which traditional Euclidean distance metrics fail to address. The combination of these two approaches results in a robust clustering framework capable of handling large-scale, high-dimensional, and noisy datasets commonly found in network intrusion detection. The proposed method was evaluated on several benchmark datasets including Darpa 1998-99, KDD Cup99, NSL-KDD, UNSW-NB15, and CAIDA. Comparative experiments with state-of-the-art algorithms such as K-Means++, K-NNDP, and DI-K-Means showed that the proposed approach consistently outperformed or matched competitors in terms of Silhouette Coefficient, Calinski-Harabasz index, and Davies-Bouldin index, indicating better cluster cohesion, separation, and compactness. Additionally, the computational efficiency gained from TILB seeding facilitates faster convergence without compromising clustering quality. Furthermore, a threshold-based cluster labeling mechanism was applied to translate clustering results into practical classifications for detecting attacks versus normal traffic, enhancing the usability of the method in real-world cybersecurity systems. Overall, this research demonstrates that the integration of TILB seeding and mutual information-based clustering provides an effective and efficient solution for network traffic classification challenges.
Co-Authors Adinda Titania Aditya Pratama, Bayu Ady Pratama, Ramadhan Alfyanang Fattulah Andi Marwan Elhanafi Ari Usman Arnes Sembiring Arnes Sembiring Arnes Sembiring Arnes Sembiring Arnes Sembiring Arnes Sembiring Arnes Sembiring Arwadi Sinuraya Asih, Munjiat Setiani Asmah Indrawati Bayu Aditya Pratama Bayu Syah, Rahmad Budi Santoso Budi Santoso Chairul Rizal Chairul Rizal Chiuloto, Kalvin Dadan Ramdan Daffa, Daffa Zain Shahriza Desi Yanti Dodi Siregar Dodi Siregar Emil Fitranshah Aliff S Erianto Ongko Eswanto, Eswanto Fera Damayanti Finta Aramita Fiqi Arfian Habib Satria Hafifah, Febri Haida Dafitri Haida Dafitri Haida Dafitri Halawa, Agung Y S Harahap, Herlina Hartono Hartono Hartono Hartono Hartono Hartono Hasibuan, Ade Zulkarnain Hasibuan, Muhammad Ridwan Hasibuan, Nasaruddin Nur Herdianto Herdianto, Herdianto Herlina Andriani Simamora Hutajulu, Olnes Yosefa Ilham Faisal Ilham Faisal Irfandi Irfandi, Irfandi Irwan Irwan Khahfi Zuhanda, Muhammad Kharunnisa Kharunnisa Lili Suryati Lubis, Husni lubis, ihsan M F Verri Anggriawan Manurung, Dionikxon Mardiatul Hasanah Marischa Elveny, Marischa Martini, Dewi Marwan Ramli Marwan Ramli Muchzakhir Bustari Mufida Khairani Mufida Khairani Muhammad Khahfi Zuhanda Muhammad Rizky Irwansyah Muhammad Zen Muhammad Zen, Muhammad Munadi Munadi Muzdalifah Ulfayani Pratama, Bayu Aditya Putra, Andre Kurnia Rachmat Aulia Rachmat Aulia, Rachmat Rahmad B.Y Syah Rahmad Syah, Rahmad Retna Astuti Kuswardani Risko Liza Ritonga, Iqbal Giffari Robby Darwis Rudi Salman Sembiring, Arnes Setyadi, Rahmat Arief Shidqi, Sultan Siregar, Rosyidah Siti Sundari Sri Eka Riyani Harahap Sultan Shidqi Sumi Khairani Suriati Suriati Suriati Suriati Suriati, Suriati Suswati suswati suswati Tanjung, Rino Nurcahyo Fauzi Tanjung, Shabila Shaharani Tengku Mhd Diansyah Tengku Mohd Diansyah, Tengku Mohd Ulfa Sahira Winanda, Icha Yasir, Amru Yessi Fitri Annisah Lubis Zealtiel, Billiam Zuhanda, M. Khahfi