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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance Firgiawan Faira; Dandy Pramana Hostiadi; Roy Rudolf Huizen
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6332

Abstract

Industry 4.0 requires secure networks as the advancements in IoT and AI exacerbate the challenges and vulnerabilities in data security. This research focuses on detecting Bot-IoT activity using the Bot-IoT UNSW Canberra 2018 dataset. The dataset initially showed a significant imbalance, with 2,934,447 entries of attack activity and only 370 entries of normal activity. To address this imbalance, an innovative data aggregation technique was applied, effectively reducing similar patterns and trends. This approach resulted in a balanced dataset consisting of 8 attack activity points and 80 normal activity points. Feature selection using the ANOVA method identified 10 key features from a total of 17: seq, stddev, N_IN_Conn_P_SrcIP, min, state_number, mean, N_IN_Conn_P_DstIP, drate, srate, and max. The classification process utilized Random Forest, k-NN, Naïve Bayes, and Decision Tree algorithms, with 100 iterations and an 80:20 training-testing split. Random Forest showed superior performance, achieving 97.5% accuracy, 97.4% precision, and 97.4% recall, with a total computation time of 11.54 seconds. Pearson correlation analysis revealed a strong positive correlation (+0.937) between N_IN_Conn_P_DstIP and seq, as well as a weak negative correlation (-0.224) between N_IN_Conn_P_SrcIP and state_number. The novelty of this research lies in the application of a data aggregation technique to address class imbalance, significantly improving machine learning model performance and optimizing training time. These findings contribute to the development of robust cybersecurity systems to effectively detect IoT-related threats.
Co-Authors Amry wicaksono, Amry Anggreni Antarajaya, I Nyoman Suraja Artamerta, Aditya Naray Candra Ahmadi, Candra Chawaphan, Pharan Danang Setyo Utomo, Danang Setyo Dian Pramana S.Kom., M.Kom, Dian Erma Sulistyo Rini Erma Sulistyo Rini, Erma Sulistyo Eva Hariyanti Evi Triandini Fatonah, Nenden Siti Firgiawan Faira Florentina Tatrin Kurniati Gede Angga Pradipta, Gede Angga Gede, Angga Pradipta Hendra Wijaya Hilmi, Muhammad Riza I G K G Puritan Wijaya. ADH, I G K G I Gede Harsemadi I Gede Ngurah Widya Pradnyana, I Gede Ngurah Widya I Gede Putu Krisna Juliharta I GKG Puritan Wijaya, I GKG I Gusti Ayu Dewi Suardi, I Gusti Ayu Dewi I Gusti Ngurah Darma Paramartha I Gusti Nym Adi Purnama Putra, I Gusti Nym I Made Darma Susila I Made Darma Susila, I Made I Made Darma Susila, I Made Darma I Nyoman Triwantara Putra, I Nyoman I Putu Harry Wibawa Eka Putra, I Putu Harry Wibawa I Putu Oka Aditya Pratama I Putu Ramayasa, I Putu I Putu Widiantara, I Putu I Wayan Eka Mahardika, I Wayan Eka I Wayan Nesa Masjaya Perdana, I Wayan Nesa I.B. Putra Utama Dhiatmika, I.B. Putra Utama Ida Bagus Suradarma Indah, Hene Nor Intaran, Arya Ngurah Kadek Evanna Sidarta, Kadek Evanna Komang Yuli Santika Made Liandana Made Liandana, Made Made Sudarma Made, Liandana Mohammad Yazdi Pusadan Muhammad Riza Hilmi Ni Ketut Dewi Ari Jayanti Ni Luh Putri Srinadi Nurfalah, Rizal Farhan Nabila Pande Wira Andika, Pande Putu Desiana Wulaning Ayu Rizky Adhitya Ridholloh, Rizky Adhitya Rosalia Hadi Roy Rudolf Huizen Rustamaji, Abdullah Saputra, Made Wisnu Adhi Shofwan Hanief Tangkawarow, Irene Tubagus Mahendra Kusuma Widhyastuti, Luh Putu Wiwien Wulaning Ayu, Putu Desiana Wulaning Ayu, Putu Desiana Yohanes Priyo Atmojo Yohanes Priyo Atmojo Yohanes Priyo Atmojo, Yohanes Yohanes Priyo Atmojo, Yohanes Priyo Yudhi Pratiwindhya, Yudhi