MCTSteg: A Monte Carlo Tree Search-Based Reinforcement Learning Framework for Universal Non-Additive Steganography. - Xianbo Mo; Shunquan Tan; Bin Li 011; Jiwu Huang (IEEE Trans. Inf. Forensics Secur., 2021)

Poster: Query-efficient Black-box Attack for Image Forgery Localization via Reinforcement Learning. - Xianbo Mo; Shunquan Tan; Bin Li 011; Jiwu Huang (CCS, 2023)

ReLOAD: Using Reinforcement Learning to Optimize Asymmetric Distortion for Additive Steganography. - Xianbo Mo; Shunquan Tan; Weixuan Tang; Bin Li 011; Jiwu Huang (IEEE Trans. Inf. Forensics Secur., 2023)

A Keyless Extraction Framework Targeting at Deep Learning Based Image-Within-Image Models. - Rongxuan Peng; Xianbo Mo; Shunquan Tan; Bin Li 011; Jiwu Huang (ICASSP, 2024)

Employing Reinforcement Learning to Construct a Decision-Making Environment for Image Forgery Localization. - Rongxuan Peng; Shunquan Tan; Xianbo Mo; Bin Li 011; Jiwu Huang (IEEE Trans. Inf. Forensics Secur., 2024)

Query-efficient Attack for Black-box Image Inpainting Forensics via Reinforcement Learning. - Xianbo Mo; Shunquan Tan; Bin Li 011; Jiwu Huang (AAAI, 2025)

Active Adversarial Noise Suppression for Image Forgery Localization. - Rongxuan Peng; Shunquan Tan; Xianbo Mo; Alex C. Kot; Jiwu Huang (CoRR, 2025)