网络与信息安全学报2026，Vol.12Issue(4)：102-114,13.DOI:10.11959/j.issn.2096-109x.AQ26055
基于分层强化学习的图像隐写检测训练方法
Hierarchical reinforcement learning-based training method for image steganalysis
摘要
Abstract
Image steganography detection is a crucial research direction in the field of digital forensics and multimedia security,aiming to accurately distinguish between cover images and steganographic images.As adaptive steganographic algorithms evolve toward low embedding rates and high undetectability,existing deep learning-based steganographic de-tection models face challenges in training strategy optimization and hyperparameter sensitivity.To address these issues,a hierarchical reinforcement learning-based training method for image steganography detection was proposed.In this method,hierarchical reinforcement learning was introduced into the training process of the steganographic detector,where high-level and low-level agents were employed to regulate episode-level and batch-level strategies,respectively.Adaptive optimization of the detector training was achieved from both the training mode and sample weighting perspec-tives.Meanwhile,a shared reward signal was constructed for the hierarchical agents based on the direct performance metrics of the detector,thereby focusing on detector performance and enabling collaborative optimization.Experimental results on the BOSSBase dataset demonstrated that the proposed method consistently improved detection performance under various embedding rate scenarios.Compared with XuNet,the proposed method increased the average detection accuracy from 87.5%to 90.0%under embedding rates ranging from 0.1 to 0.5 bpp,and it was also compatible with more powerful steganographic detectors such as SRNet and Yedroudj-Net.Ablation studies validated the effectiveness of the state space design and the hierarchical architecture in the proposed method.关键词
图像隐写检测/训练策略优化/分层强化学习Key words
image steganography detection/training strategy optimization/hierarchical reinforcement learning分类
信息技术与安全科学引用本文复制引用
任德翔,杨荣健,卢晓珍,方黎明..基于分层强化学习的图像隐写检测训练方法[J].网络与信息安全学报,2026,12(4):102-114,13.基金项目
国家自然科学基金资助项目(No.U22B2062,No.62571240,No.U22B2029,No.62272228) （No.U22B2062,No.62571240,No.U22B2029,No.62272228）
江苏省前沿引领技术基础研究重大项目(No.BK20222001) （No.BK20222001）
东南大学移动通信全国重点实验室开放研究基金资助课题(No.2026D06)The National Natural Science Foundation of China(No.U22B2062,No.62571240,No.U22B2029,No.62272228),Major Project for Frontier Leading Technology Basic Research of Jiangsu Province(No.BK20222001),The Open Research Fund of the National Mobile Communications Research Laboratory of Southeast University(No.2026D06) （No.2026D06）
