Deep Neural Networks for Malicious JavaScript Detection Using Bytecode Sequences. - Muhammad Fakhrur Rozi; Sangwook Kim; Seiichi Ozawa (IJCNN, 2020)

JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism. - Muhammad Fakhrur Rozi; Tao Ban; Seiichi Ozawa; Sangwook Kim; Takeshi Takahashi 001; Daisuke Inoue (ICONIP (2), 2021)

Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation. - Muhammad Fakhrur Rozi; Tao Ban; Seiichi Ozawa; Akira Yamada 001; Takeshi Takahashi 001; Sangwook Kim; Daisuke Inoue (IEEE Access, 2023)

Learning to Unfix: Towards ML Robustness in Vulnerability Detection via Structure-Aware Code Generation. - Muhammad Fakhrur Rozi; Takeshi Takahashi 001 (ACSAC Workshops, 2024)

Securing Code With Context: Enhancing Vulnerability Detection Through Contextualized Graph Representations. - Muhammad Fakhrur Rozi; Tao Ban; Seiichi Ozawa; Akira Yamada 001; Takeshi Takahashi 001; Daisuke Inoue (IEEE Access, 2024)