selected papers主要論文
- Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Akira Yamada, Takeshi Takahashi, Sangwook Kim, and Daisuke Inoue, "Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation," IEEE ACCESS, September 2023. （Impact Factor: 3.9 (2023））
- Tao Ban, Takeshi Takahashi, Samuel Ndichu, and Daisuke Inoue, ''Breaking Alert Fatigue: AI-Assisted SIEM Framework for Effective Incident Response,'' Applied Sciences, 13(11), 6610, May 2023. （Impact Factor: 2.7 (2022））.
- Muhammad Fakhrur Rozi, Seiichi Ozawa, Tao Ban, Sangwook Kim, Takeshi Takahashi, and Daisuke Inoue, ''Understanding the Influence of AST-JS for Improving Malicious Webpage Detection,'' Applied Sciences, Dec., 2022.（Impact Factor: 2.7 (2022)）
- Samuel Ndichu, Tao Ban, Takeshi Takahashi and Daisuke Inoue, ''AI-Assisted Security Alert Data Analysis with Imbalanced Learning Methods,'' Appl. Sci., February 2023. （Impact Factor: 2.838 (2021））
- Chia-Yi Wu, Tao Ban, Shin-Ming Cheng, Takeshi Takahashi, Daisuke Inoue, ''IoT Malware Classification Based on Reinterpreted Function-Call Graphs,'' Computer & Security, Elsevier. （Impact Factor: 5.105 (2021））
- B. Sun, T. Ban, C. Han, T. Takahashi, K. Yoshioka, J. Takeuchi, A. Sarrafzadeh, M. Qiu, and D. Inoue, ''Leveraging Machine Learning Technique to Identify Deceptive Decoy Documents Associated with Targeted Email Attacks,'' IEEE ACCESS, 2021.
- Tzu-Ling Wan, Tao Ban, Shin-Ming Cheng, Yen-Ting Lee, Bo Sun, Ryoichi Isawa, Takeshi Takahashi, and Daisuke Inoue, "An Efficient Approach to Detect and Classify IoT Malware Based on Byte Sequences from Executable Files," IEEE Open Journal of the Computer Society, Vol. 1, pp. 262-275, Oct. 2020.
