Invariances of JPEG-quantized DCT coefficients and their application in robust image steganography

Zhu, Liyan; Luo, Xiangyang; Yang, Ching-Nung; Zhang, Yi; Liu, Fenlin

doi:10.1016/j.sigpro.2021.108015

Cited by 29 publications

(14 citation statements)

References 20 publications

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“…In least significant bit (LSB) based data hiding, the LSBs of pixel values [1][2][3][4][5] or high-frequency coefficients [6][7] are used as the holder of information bits. In [1][2][3][4][5], it works by replacing the LSBs of randomly selected pixels in the host image with secret message bits.…”

Section: Fig 1 a Simple Model Of Information Hidingmentioning

confidence: 99%

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Large-Capacity Image Data Hiding based on Table Look-up

Ding¹,

Zhang²,

Reulke³

et al. 2021

Preprint

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In previous data hiding techniques, binary rules are usually used to guide the fine-tuning of the values of basic objects in the host media to hide bit 0 and bit 1. In this paper, we propose a new data hiding technique for gray images based on querying a 256x256 information table. The information table is constructed by cloning a 3x3 basic block, which we call seed block. Eight unsigned integer values between 0 and 7, i.e., 3 bit binary data, are assigned to different elements of the seed block. Each time, a pair of pixels are chosen from a host image, and their pixel values are used as row and column numbers to look up the information table. If element value obtained by looking up the table is equal to the 3 bit binary data to be hidden, the values of the pixel pair will remain unchanged. Otherwise, take this element as the central point, we call it the focus element, to enclose a 3x3 window in the information table. Then in the window, find the element which is equal to the data to be hidden. Finally, update the pixel values of the pair with the row and column numbers of the found element in the window. Since the row and column numbers are in the range of 0-255, the updated pixel values will not overflow. In the proposed algorithm, a pair of pixels can hide 3 bits of information, so the embedding capacity is very high. Since the adjustment of pixel values is constrained in a 3x3 window, the modification amount of pixel values is small. The proposed technique belongs to fragile digital watermarking, so it can be used for image authentication and tamper localization. By the evaluation of data hiding capacity, security, imperceptibility, computational cost and extensibility, this algorithm is superior to existing information hiding techniques. The proposed technique can also be used in color image and audio data hiding.

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Section: Fig 1 a Simple Model Of Information Hidingmentioning

confidence: 99%

“…5. From Table 1, we can see that from focus element to four elements (6,7,4,3), the sum of changes in x and y is 2; while from focus element to other four elements (0, 1, 5, 0), the sum of changes in x and y is only 1.…”

Section: Construction Of Informationmentioning

confidence: 99%

Large-Capacity Image Data Hiding based on Table Look-up

Ding¹,

Zhang²,

Reulke³

et al. 2021

Preprint

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“…e penultimate step is valid because of an application of equation (12). e last step is valid since the independence of the steganographic key K, data M, distortion function T, and cover object X.…”

Section: Theoremmentioning

confidence: 99%

“…e adaptive steganography based on STC (Syndrome-Trellis Codes) [8] has a high antidetection performance by embedding data into complex texture areas that are difficult to model and has been a mainstream direction in the field of information hiding in recent years. At present, many STC-based adaptive steganography algorithms [9][10][11][12][13] have been proposed. However, there have been a few studies [14][15][16] that could extract data from STC-based adaptive steganography in specific scenarios, indicating that such algorithms may have hidden security risks.…”

Section: Introductionmentioning

confidence: 99%

“…Hopper [18] studied the problem of covert security from the perspective of cryptography and defined covert security from the perspective of computational complexity under the assumption of passive aggression. As the problem of data extraction was put forward, some scholars [3,[9][10][11][12] pointed out that steganography should not only have covert security but also have cryptographic secrecy.…”

Section: Introductionmentioning

confidence: 99%

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Cryptographic Secrecy Analysis of Adaptive Steganographic Syndrome-Trellis Codes

Du¹,

Liu²,

Tian³

et al. 2021

Security and Communication Networks

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Compared with traditional steganography, adaptive steganography based on STC (Syndrome-Trellis Codes) has extremely high antidetection ability and has been a mainstream and hot research direction in the field of information hiding over the past decades. However, it is noted, in specific scenarios, that a small number of methods can extract data from STC-based adaptive steganography, indicating security risks related to such algorithms. In this manuscript, the cryptographic secrecy of this kind of steganography is analyzed, on condition of two common attacks: stego-only attack and known-cover attack, respectively, from three perspectives: steganographic key equivocation, message equivocation, and unicity distance of the steganographic key. Focusing on the special layout characteristics of the parity-check matrix of STC, under the two attack conditions, the theoretical boundaries of the steganographic key equivocation function, the message equivocation function, and the unicity distance of the steganographic key are separately obtained, showing the impact of the three elements: the submatrix size, the randomness of the data, and the cover object on the cryptographic secrecy of the STC-based adaptive steganography, resulting in a theoretical reference to accurately judge the cryptographic secrecy of such steganography and design more secure steganography methods.

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A survey of recent advances in image steganography

Kumar

Rani

Singh

2022

Security and Privacy

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Over the course of technological development, data security while transmission and storing has always been a field of continuous advancements and key importance. In the recent times, its importance has increased even further and the main reason behind this is the increase in the amount of data that is being transferred over internet and various networks. Although there are cryptographic approaches to handle these situations, steganography provides a different aspect to the solution. While cryptography encrypts the data such that the cipher text is visible to human eye, but the meaning of that encrypted text is never known. Steganography is the process of hiding data in plain sight inside some images, audio, video and so on, such that it is very difficult for the viewer to directly differentiate if there is some data hidden in the host or not. This paper consists a study of various methodologies to implement Image steganography like spatial domain manipulation, encryption based and deep learning approaches. The paper focuses upon recent advances in all these approaches for image steganography and aims to help other researches in this domain to understand recent developments as well future advancements possible in the same field. Furthermore, this paper illustrates about how different image formats effect various image steganography methods and how the various image color models interact with image steganography. Later this article sheds some light on the domain of steganalysis and reports about the fundamental principles as well as various implementations of steganalysis systems in recent times.

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Invariances of JPEG-quantized DCT coefficients and their application in robust image steganography

Cited by 29 publications

References 20 publications

Large-Capacity Image Data Hiding based on Table Look-up

Large-Capacity Image Data Hiding based on Table Look-up

Cryptographic Secrecy Analysis of Adaptive Steganographic Syndrome-Trellis Codes

A survey of recent advances in image steganography

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