Multibit Embedding Algorithm for Steganography of Palette-Based Images

Imaizumi, Shoko; Ozawa, Koichiro

doi:10.1007/978-3-642-53842-1_9

Cited by 8 publications

(3 citation statements)

References 10 publications

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“…Steganography is primarily the art of concealing certain secret data by embedding it into a host-or cover-image medium. Steganography for image processing can be divided into spatial as in [28], [29], transformation-based domain techniques in [30], and adaptive steganography methods in [31]- [34]. A stego-image can be produced utilizing numerous steganography algorithms to conceal information, as demonstrated in practical [35].…”

Section: Hybrid Approach To Steganalysis a Transformsmentioning

confidence: 99%

Toward Hybrid Classical Deep Learning-Quantum Methods for Steganalysis

Wardhani,

Putranto,

et al. 2024

IEEE Access

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This paper explores the potential of the hybrid classical deep learning quantum in addressing contemporary information security challenges, including cyber-attack detection and prevention, botnet detection, IP-theft, hardware defect detection, and more, with a specific emphasis on steganalysis. We begin by offering a succinct overview of current information security research trends, focusing on the hybrid classical deep learning-quantum paradigm. Subsequently, we introduce a classical-quantum hybrid framework tailored for uncovering concealed information within a significant public steganalysis dataset, ALASKA2. To enable image extraction and classification, we present a two-layer architecture that integrates convolutional neural network layers into both the classical deep learning and quantum layers. Notably, the proposed approach has improved steganalysis accuracy by achieving a 97% implementation accuracy rate.

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Section: Hybrid Approach To Steganalysis a Transformsmentioning

confidence: 99%

Toward Hybrid Classical Deep Learning-Quantum Methods for Steganalysis

Wardhani,

Putranto,

et al. 2024

IEEE Access

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“…He [34] proposed a combination of PVD, MF, and particle swarm optimization. Alongside LSB and PVD, there are numerous other traditional methods being developed, such as histogram shifting [35,36], multiple-bit planes [37], and palettes [38]. In addition to the aforementioned traditional methods, deep learning is emerging as an effective approach for information hiding in images.…”

Section: Overview Of Related Workmentioning

confidence: 99%

Model of Message Transmission across Parallel Route Groups with Dynamic Alternation of These Groups in a Multichannel Steganographic System

Ha,

Tran,

Shichkina

2023

Electronics

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The subject of this study is steganographic systems that are able to hide not only the content of the transmitted information but also the fact of its transmission. In this paper, we present a novel data transmission model within such systems, combining a modified Dijkstra’s algorithm with the dynamic utilization of multiple transmission routes. Consequently, this allows the simultaneous transmission of messages through parallel groups of routes with the dynamic alternation of these groups during the information exchange process between the sender and the receiver in the steganographic network. Thus, the speed, reliability, and security of message transmission are improved. Moreover, to increase the security level, the proposed model uses a route–time matrix that is available only to the sender and receiver. Additionally, the data transmission model has been tested on synthetic data and data obtained from real devices. The evaluation of the effectiveness of the proposed model on the example of various structured steganographic systems shows the significant effectiveness of our model. As a result, in comparison with existing similar methods, the secrecy index was increased five times and the violation index was decreased four times.

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“…Of these media, images are the most popular because they are widely transmitted over the Internet. Many image-based steganography methods [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] have been proposed and applied in raw [1][2][3][4][5], JPEG [6], VQ [7], and absolute moment block truncation coding (AMBTC) [8] images. However, the application in palette images [9][10][11][12][13][14][15][16][17] is limited.…”

Section: Introductionmentioning

confidence: 99%

Block-Based Steganography Method Using Optimal Selection to Reach High Efficiency and Capacity for Palette Images

Chen

Ching

2020

Applied Sciences

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The primary goal of steganographic methods is to develop statically undetectable methods with high steganographic capacity. The embedding efficiency is one kind of measure for undetectability. Block-based steganography methods have been proposed for achieving higher embedding efficiency under limited embedding capacity. However, in these methods, some blocks with larger embedding distortions are skipped, and a location map is usually incorporated into these methods to record the embedding status of each block. This reduces the embedding capacity for secret messages. In this study, we proposed a block-based steganography method without a location map for palette images. In this method, multiple secret bits can be embedded in a block by modifying at most one pixel with minimal embedding distortion; this enables each block to be used for data embedding; thus, our method provides higher embedding capacity. Furthermore, under the same capacity, the estimated and experimental embedding efficiencies of the proposed method are compared with those of Imaizumi et al. and Aryal et al.’s methods; the comparisons indicate that the proposed method has higher embedding efficiency than Imaizumi et al. and Aryal et al.’s methods.

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Multibit Embedding Algorithm for Steganography of Palette-Based Images

Cited by 8 publications

References 10 publications

Toward Hybrid Classical Deep Learning-Quantum Methods for Steganalysis

Toward Hybrid Classical Deep Learning-Quantum Methods for Steganalysis

Model of Message Transmission across Parallel Route Groups with Dynamic Alternation of These Groups in a Multichannel Steganographic System

Block-Based Steganography Method Using Optimal Selection to Reach High Efficiency and Capacity for Palette Images

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