TAO BAN

Chief Senior Researcher
Center for Research on AI Security and Technology Evolution

Chief Senior Researcher
Cybersecurity Laboratory, Cybersecurity Research Institute

Dr. Tao Ban received his B.E. degree from Xi'an Jiaotong University in 1999, M.E. degree from Tsinghua University in 2003, and Ph.D. degree from Kobe University in 2006, respectively. He is currently a senior researcher at the Cybersecurity Research Institute, National Institute of Information and Communications Technology, Tokyo, Japan. He is engaged in research on cybersecurity technologies such as live network observation, efficient incident response, and malware analysis of IoT devices using machine learning. His research interests also include network security, machine learning, and data mining.

Research interests: Cybersecurity
Keyword: Malware analysis, alert screening, NIDS

Selected papers

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.

Awards

APNNS Excellent Service Award, ASIA Pacific Neural Network Society, 2020
Best Paper Award, IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, 2020
Conceptual Research Award, 23rd Computer Security Symposium, 2020
Outstanding Leadership Award, 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 2020
Best paper award, The 13th Asia Joint Conference on Information Security, 2018
Information and Communication System Security, Research Award, 2013
Best paper award, The 8th Asia Joint Conference on Information Security, 2013
Best paper award, IEEE DMAI, 2008
Best paper award, ICONIP, 2007
IEEE Kansai Branch Student Research Award, 2006

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