Adversarial Embedding Steganography via Progressive Probability Optimizing and Discarded Stego Recycling

IF 3.2 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Signal Processing Letters Pub Date : 2024-10-10 DOI:10.1109/LSP.2024.3478109
Fan Wang;Zhangjie Fu;Xiang Zhang;Junjie Lu
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Abstract

Adversarial embedding for image steganography is a novel technology to effectively enhance the steganographic security of the traditional steganographic algorithms. However, the existing schemes still have room for further improvement in the design of optimization strategy and the steganographic post-processing of optimization failure. In this paper, we design the progressive probability optimizing strategy (PPO). It dynamically selects more efficient gradients to guide the optimization of the probability optimization in a progressive manner. Moreover, we propose a discarded stego recycling mechanism (DSR) to re-select the stego from the discarded stego set that have failed to deceive the target steganalyzer after the optimzation fails. In such way, the statistical distribution of the stego can still further approximate the cover, thus further improving the steganographic security on re-trained steganalyzers in adversary-aware scenario. Comprehensive experiments show that compared with the existing advanced schemes, the proposed method boosts the security improvement against both the re-trained hand-crafted feature-based and deep leanring-based steganalysis models.
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通过渐进概率优化和丢弃式偷窃回收实现逆向嵌入式隐写术
逆向嵌入图像隐写术是一种新型技术,能有效提高传统隐写算法的隐写安全性。然而,现有方案在优化策略设计和优化失败的隐写后处理方面仍有进一步改进的空间。本文设计了渐进概率优化策略(PPO)。它能动态选择更有效的梯度,以渐进的方式指导概率优化。此外,我们还提出了一种丢弃的隐去再循环机制(DSR),在优化失败后,从丢弃的隐去集中重新选择未能欺骗目标隐分析仪的隐去。这样,隐果的统计分布仍能进一步逼近封面,从而进一步提高了在对手感知场景下重新训练的隐分析仪的隐写安全性。综合实验结果表明,与现有的先进方案相比,所提出的方法在对抗重新训练的基于手工特征的隐写分析模型和基于深度精简的隐写分析模型时,都提高了安全性。
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来源期刊
IEEE Signal Processing Letters
IEEE Signal Processing Letters 工程技术-工程:电子与电气
CiteScore
7.40
自引率
12.80%
发文量
339
审稿时长
2.8 months
期刊介绍: The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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