High-Capacity Image Steganography Based on Improved FC-DenseNet

Duan, Xintao; Liu, Nao; Gou, Mengxiao; Yue, Dongli; Xie, Zimei; Ma, Yuanyuan; Qin, Chuan

doi:10.1109/access.2020.3024193

Cited by 30 publications

(15 citation statements)

References 30 publications

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“…The proposed scheme replaces the extraction network with a structure similar to the hiding network, which improves the performance of the decryption network. Therefore, the proposed TRPSteg is also clearly different from the previous CNNbased image steganography schemes [15][16][17]. In addition, a novel strategy of recursive permutation is proposed to encrypt the secret image and further improve the security of the steganography model.…”

Section: Differences Between Trpsteg and Other Image Steganography Sc...mentioning

confidence: 90%

“…However, these works have one or more of the following shortcomings: (1) the colors of the generated steganographic images are distorted [18]; (2) the hiding capacity is limited in [15,[18][19][20][21]. (3) the model [15][16][17]22] does not fit the steganographic process well; and (4) the secret image is not encrypted and then steganographic in [16,21,23]; thus, it is not sufficiently secure.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Deep Image Steganography Using Transformer and Recursive Permutation

Wang

Zhou

Liu

et al. 2022

Entropy

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Image steganography, which usually hides a small image (hidden image or secret image) in a large image (carrier) so that the crackers cannot feel the existence of the hidden image in the carrier, has become a hot topic in the community of image security. Recent deep-learning techniques have promoted image steganography to a new stage. To improve the performance of steganography, this paper proposes a novel scheme that uses the Transformer for feature extraction in steganography. In addition, an image encryption algorithm using recursive permutation is proposed to further enhance the security of secret images. We conduct extensive experiments to demonstrate the effectiveness of the proposed scheme. We reveal that the Transformer is superior to the compared state-of-the-art deep-learning models in feature extraction for steganography. In addition, the proposed image encryption algorithm has good attributes for image security, which further enhances the performance of the proposed scheme of steganography.

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Section: Differences Between Trpsteg and Other Image Steganography Sc...mentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Deep Image Steganography Using Transformer and Recursive Permutation

Wang

Zhou

Liu

et al. 2022

Entropy

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“…One LSB is the most appropriate way of hiding information because of its reversibility, or you can say that robustness against different attacks [4]. This work mainly focuses on image steganography [5]. Therefore, the term cover object now becomes cover image.…”

Section: System Modelmentioning

confidence: 99%

Reversible Secured Data Hiding using Binary Encryption and Digital Bit Modification Scheme

Waykole¹

2022

tjes

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The information is getting precious day by day because of the digital revolution and more reach exposure of citizens to technology. The security of information is in demand and the topmost priority among researchers to develop data security systems. Image steganography is one of the data hiding schemes which is invisible in nature, although it uses visible image media to hide information. Steganography is not only limited to images. There are other media like text, audio, or video that can be utilized for hiding information. In this research work, a novel data hiding is being developed using an image as cover media. Researchers are facing during the development of the technique is maintaining the payload capacity as well as higher PSNR values and other parameters. This work uses colour images as cover and digital bit modification methods to hide secure information. Only hiding is not enough to secure information. There is an additional layer of security added by encrypting a secure message using an encryption method. The digital bit modification method is unconventionally spread the sequential bitstream over channels. This would make this approach unique and better as it is keeping the PSNR level higher along with NCC and lower MSE. All this is done by keeping the payload capacity as the maximum available. The average value of PSNR is 60.295dB, NCC is 1.00, and MSE is 0.1567.

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“…Given the value of being able to hide the existence of data, researchers propose a range of stenographic techniques that work at various levels of the system stack. The most popular techniques work at the system level, hiding data in images [12,53], audio files [54], video files [40], and within file system metadata [5,30,35]. Another set of techniques hides data in the transmission of cover data across a network [55].…”

Section: Introductionmentioning

confidence: 99%

Invisible bits: hiding secret messages in SRAM’s analog domain

Mahmod

Hicks

2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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Electronic devices are increasingly the subject of inspection by authorities. While encryption hides secret messages, it does not hide the transmission of those secret messagesÐin fact, it calls attention to them. Thus, an adversary, seeing encrypted data, turns to coercion to extract the credentials required to reveal the secret message. Steganographic techniques hide secret messages in plain sight, providing the user with plausible deniability, removing the threat of coercion.This paper unveils Invisible Bits a new steganographic technique that hides secret messages in the analog domain of Static Random Access Memory (SRAM) embedded within a computing device. Unlike other memory technologies, the power-on state of SRAM reveals the analog-domain properties of its individual cells. We show how to quickly and systematically change the analog-domain properties of SRAM cells to encode data in the analog domain and how to reveal those changes by capturing SRAM's power-on state. Experiments with commercial devices show that Invisible Bits provides over 90% capacityÐtwo orders-of-magnitude more than previous on-chip steganographic approaches, while retaining device functionalityÐeven when the device undergoes subsequent normal operation or is shelved for months. Experiments also show that adversaries cannot differentiate between devices with encoded messages and those without. Lastly, we show how to layer encryption and error correction on top of our message encoding scheme in an end-to-end demonstration. CCS CONCEPTS• Hardware → Communication hardware, interfaces and storage; • Security and privacy → Pseudonymity, anonymity and untraceability.

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High-Capacity Image Steganography Based on Improved FC-DenseNet

Cited by 30 publications

References 30 publications

Deep Image Steganography Using Transformer and Recursive Permutation

Deep Image Steganography Using Transformer and Recursive Permutation

Reversible Secured Data Hiding using Binary Encryption and Digital Bit Modification Scheme

Invisible bits: hiding secret messages in SRAM’s analog domain

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