Errorless robust JPEG steganography using steganographic polar codes

IF 2.5 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS EURASIP Journal on Information Security Pub Date : 2024-07-04 DOI:10.1186/s13635-024-00173-4
Jimin Zhang, Xiaolei He, Yun Cao
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Abstract

Recently, a robust steganographic algorithm that achieves errorless robustness against JPEG recompression has been proposed. The method employs a lattice embedding scheme and utilizes the syndrome-trellis code (STC) for practical embedding. However, we have noticed that errorless robust embedding with STC may encounter failures due to modifications on wet coefficients, especially when a high quality factor is used by the compression channel. To solve this problem, we have discovered that using steganographic polar code (SPC) for embedding has better performance in avoiding modifications on wet coefficients. In this paper, we conduct theoretical analysis to prove the better performance of SPC in wet paper embedding. We establish the condition of avoiding modifications on wet coefficients, followed by presenting a recursive calculation method for determining the distribution of columns in the generator matrix of SPC. The findings reveal that SPC can avoid modifications on wet coefficients under a larger number of wet coefficients compared with STC, and therefore we propose a better errorless robust embedding method employing SPC. The experimental results demonstrate that under close security performance, the proposed method achieves a higher success rate compared with embedding with STC. Specifically, when the quality factor of the compressor is 95 and the payload size is 0.4 bpnzac, our method achieves a success rate of 99.85%, surpassing the 91.95% success rate of the embedding with STC.
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使用极性隐写代码的无差错稳健型 JPEG 隐写术
最近,有人提出了一种稳健的隐写算法,该算法可实现对 JPEG 重压缩的无差错稳健性。该方法采用网格嵌入方案,并利用综合征-特雷利斯码(STC)进行实际嵌入。然而,我们注意到,使用 STC 的无差错稳健嵌入可能会因为对湿系数的修改而失败,尤其是当压缩通道使用高品质因数时。为了解决这个问题,我们发现使用极性隐写码(SPC)进行嵌入在避免对湿系数的修改方面具有更好的性能。本文通过理论分析证明了 SPC 在湿纸嵌入中的更好性能。我们建立了避免修改湿系数的条件,然后提出了一种确定 SPC 生成矩阵中列分布的递归计算方法。研究结果表明,与 STC 相比,SPC 可以在更多湿系数的情况下避免对湿系数的修改,因此我们提出了一种采用 SPC 的更好的无差错鲁棒嵌入方法。实验结果表明,在安全性能接近的情况下,与使用 STC 的嵌入方法相比,所提出的方法获得了更高的成功率。具体来说,当压缩器的质量系数为 95、有效载荷大小为 0.4 bpnzac 时,我们的方法达到了 99.85% 的成功率,超过了使用 STC 进行嵌入的 91.95% 的成功率。
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来源期刊
EURASIP Journal on Information Security
EURASIP Journal on Information Security COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
8.80
自引率
0.00%
发文量
6
审稿时长
13 weeks
期刊介绍: The overall goal of the EURASIP Journal on Information Security, sponsored by the European Association for Signal Processing (EURASIP), is to bring together researchers and practitioners dealing with the general field of information security, with a particular emphasis on the use of signal processing tools in adversarial environments. As such, it addresses all works whereby security is achieved through a combination of techniques from cryptography, computer security, machine learning and multimedia signal processing. Application domains lie, for example, in secure storage, retrieval and tracking of multimedia data, secure outsourcing of computations, forgery detection of multimedia data, or secure use of biometrics. The journal also welcomes survey papers that give the reader a gentle introduction to one of the topics covered as well as papers that report large-scale experimental evaluations of existing techniques. Pure cryptographic papers are outside the scope of the journal. Topics relevant to the journal include, but are not limited to: • Multimedia security primitives (such digital watermarking, perceptual hashing, multimedia authentictaion) • Steganography and Steganalysis • Fingerprinting and traitor tracing • Joint signal processing and encryption, signal processing in the encrypted domain, applied cryptography • Biometrics (fusion, multimodal biometrics, protocols, security issues) • Digital forensics • Multimedia signal processing approaches tailored towards adversarial environments • Machine learning in adversarial environments • Digital Rights Management • Network security (such as physical layer security, intrusion detection) • Hardware security, Physical Unclonable Functions • Privacy-Enhancing Technologies for multimedia data • Private data analysis, security in outsourced computations, cloud privacy
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