JPEG image steganography payload location based on optimal estimation of cover co-frequency sub-image

Wang, Jie; Yang, Ching-Nung; Zhu, Ma; Song, Xiaocheng; Liu, Yuan; Lian, Yuemeng

doi:10.1186/s13640-020-00542-2

Cited by 24 publications

(3 citation statements)

References 23 publications

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“…To verify the effectiveness of the proposed location method in this paper, we conduct experiments on the baseline Bossbase 1.01 dataset [47]. It contains 10,000 images in 512 × 512 8 bit grayscale (PGM format) from eight different digital cameras.…”

Section: Resultsmentioning

confidence: 99%

“…Meanwhile, to enhance the accuracy of payload location, the idea of maximum posterior probability was proposed. However, the location performance is not optimal in [40], which can be improved [47]. Without the loss of generality, the linear correlation among the corresponding DCT coefficients in the subimage is not as remarkable as that among the neighboring pixels in the spatial domain.…”

Section: Related Workmentioning

confidence: 98%

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Novel Hidden Bit Location Method towards JPEG Steganography

Pan

Qiao

et al. 2022

Security and Communication Networks

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Image steganalysis has been widely studied, most of which can only complete the binary task of identifying the existence of hidden bits in an inquiry image. Currently, although some algorithms have been proposed to locate hidden bits, most of them mainly focus on the spatial domain, while usually ignoring the study of locating secret bits hidden in DCT domain for JPEG image. To address that challengeable problem, in this paper, towards two classical steganographic algorithms JSteg and F5, hiding bits in DCT domain, we propose a novel payload location method. The principal step of payload location is to estimate the cover image. We novelly propose to assign the different weights to the DCT coefficient residual in virtue of the texture of regions measured by the local variance, leading to the remarkable improvement of location results. Compared with the state of the art, the numerical experiments empirically verify that our proposed location method achieves the superior performance. In particular, when locating hidden bits in JSteg steganographic images with quality factor of 95 at the payload 0.1, the accuracy of location is remarkably improved from 46.18% to 90.22%.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 98%

Novel Hidden Bit Location Method towards JPEG Steganography

Pan

Qiao

et al. 2022

Security and Communication Networks

Self Cite

View full text Add to dashboard Cite

show abstract

“…Also, the following established algorithms obey the rule of binary classification by using hand-crated SPAM features [40] of [41] or deep-learning-based features [42]. Recently, [43,44] propose locating hidden bits in the DCT domain, mainly targeting JSteg and F5 steganography, whose stego key can be recovered in [45].…”

Section: Introductionmentioning

confidence: 99%

Toward Steganographic Payload Location via Neighboring Weight Algorithm

Qiao

Luo

Pan

et al. 2022

Security and Communication Networks

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Modern steganalysis has been widely investigated, most of which mainly focus on dealing with the problem of detecting whether an inquiry image contains hidden information. However, few articles in the literature study the location of secret bits hidden by modern adaptive steganography. In this paper, we propose a novel algorithm for locating steganographic payload in the spatial domain. We first predict the steganographic scheme and its payload, which is used for generating a random bitstream. Then, the random bits are embedded in the stego image based on the cost matrix in the framework of Syndrome-Trellis Codes (STCs). Next, relying on the differences between two stego images, the extended modification map in couple with the neighboring weight algorithm can be acquired, leading to the location of the hidden bits. Compared with the prior art, the extensive experiments verify that our proposed locating algorithm performs better, in terms of locating accuracy and efficiency.

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