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Network Intrusion Detection Using Transformer Models and Natural Language Processing for Enhanced Web Application Attack Detection Wowon Priatna; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.82462

Abstract

The increasing frequency and complexity of web application attacks viralslot necessitate more advanced detection methods. This research explores integrating Transformer models and Natural Language Processing (NLP) techniques to enhance network intrusion detection systems (NIDS) viralslot. Traditional NIDS often rely on predefined signatures and rules, limiting their effectiveness against new attacks. By leveraging the Transformer's ability to capture long-term dependencies and the contextual richness of NLP, this study aims to develop a more adaptive and intelligent intrusion detection framework. Utilizing the CSIC 2010 dataset, comprehensive preprocessing steps such as tokenization, stemming, lemmatization, and normalization were applied. Techniques like Word2Vec, BERT, and TF-IDF were used for text representation, followed by the application of the Transformer architecture. Performance evaluation using accuracy, precision, recall, F1 score, and AUC demonstrated the superiority of the Transformer-NLP model over traditional machine learning methods. Statistical validation through Friedman and T-tests confirmed the model's robustness and practical significance. Despite promising results, limitations include the dataset's scope, computational complexity, and the need for further research to generalize the model to other types of network attacks. This study indicates significant improvements in detecting complex web application attacks viralslot, reducing false positives, and enhancing overall security, making it a viable solution for addressing increasingly sophisticated cybersecurity threats
Co-Authors Adi Setiawan Adi Winarta, Adi Andreas A. Febrianto Andreas Ardian Febrianto Andreas Febrianto Apriansa, Farul April Lia Hananto Ardilla Ayu Dewanti Ridwan Arif Darmawan Baihaqi, Kiki Ahmad Danny Manongga Deddy Susilo Demas Sabatino Deny Christian Dhanar Intan Surya Saputra Eduard Royce Efraim Anggriyono Eko Sediyono Eva Yovita Dwi Utami Farica, Jevan Fauzi Ahmad Muda Fernanda, Denis Aditya Filda Angellia Fransiscus Dalu Setiaji Gunawan Dewantoro Hartanto Kusuma Wardana Henderi . Hendry Heri Setiawan Hindriyanto Dwi Purnomo Ignatius Agus Supriyono Ilham Hizbuloh Irwan Sembiring Ivanna Kristianti Timotius Joko Siswanto Jonatan, Jeany Johana Junias Robert Gultom Kevin Ananta Kuntadi Widiyoko Larasati, Dwira Kurnia Maria Enggar Santika Millenika, Prayudha Mohammad Ridwan Ninda Lutfiani Onix Setyawan, Revivo Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purnomo, Hendryanto Dwi Regina Lionnie Ridwan, Ridwan Romli Jumpai Panggabean Rudi Laksono Santoso, Joseph Teguh Santoso, Yosef Karuna Saptadi Nugroho Sarumaha, Asisman Sembiring, Jenda Suranta Septian Abednego Simanjuntak, Sarida Hotdeliana Simbolon, Winda C Sinaga, Ester Ronida Sirilus Widi Surya Pranata Sukoco, Septyan Eko Hardyan Saputra Sulistio Sulistio Sutina, I Wayan Theodorus Leo Hartono Theopillus J. H. Wellem Tri Mulyanto Tri Wahyuningsih Trisno Sri Suparyati Soenarto dan Dibyo Pramono Agung Wibowo Untung Rahardja Wibowo, Mars Caroline Winny purbaratri Yaqien, Angga Ainul Yayi Suryo Prabandari Yulianto, Eko Susetyo Zainal Arifin Hasibuan Zalukhu, Pasrah