MUHAMMAD FAKHRUR ROZI

Researcher
Center for Research on AI Security and Technology Evolution

Researcher
Cybersecurity Laboratory, Cybersecurity Research Institute

He completed his master's degree in Electrical and Electronics Engineering at the Graduate School of Engineering, Kobe University, in 2021. He then directly continued his cybersecurity studies at the same university to pursue his doctoral degree. At the same time, he also joined the cybersecurity laboratory in NICT as a researcher specifying in AI in cybersecurity research group.

His research interest is web security, such as malicious JavaScript, phishing detection, and malicious URL analysis. He tries to bring AI as a novel approach to solving web security problems. He was a part of a WarpDrive project from 2019 to 2021 that aimed to develop a web-mediated attack countermeasure technology. Currently, he is working on improving malicious webpage detection and obfuscation of JavaScript code analysis.

Research interests: Websecurity, Phishing Websites, Graph for Cybersecurity, Malicious JavaScript
Keyword: malicious JavaScript, phishing, malicious URL detection

Selected papers

M. F. Rozi, T. Ban, S. Ozawa, S. Kim, T. Takahashi, D. Inoue, "JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism." International Conference on Neural Information Processing. Springer, Cham, 2021.
M. F. Rozi, T. Ban, S. Kim, S. Ozawa, T. Takahashi, D. Inoue, "Detecting Malicious Websites Based on JavaScript Content Analysis, " In Proceedings of the Computer Security Symposium, 727-732, 2021
M. F. Rozi, S. Ozawa, S. Kim, "Deep neural networks for malicious JavaScript detection using bytecode sequences," In Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2020

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