A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques

Hameed, Mohamed Abdel; Abdel-Aleem, Omar A.; Hassaballah, M.

doi:10.1007/s12652-022-04366-y

Cited by 27 publications

(3 citation statements)

References 58 publications

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“…To meet the rising computational power of cryptanalysis, encryption methods have been considerably improved to increase their complexity, preventing attackers from quickly compromising encrypted data [3,4]. As a result, digital picture scramblers are meant to convert clear images into unintelligible ones as an integral part of modern data protection measures such as image encryption [5,6], steganography [7][8][9][10][11], and watermarking [12][13][14]. Encryption and cryptography stand at the forefront of efforts to protect sensitive information from unauthorized access, ensuring that data remains confidential and unaltered after transmission over networks.…”

Section: Introductionmentioning

confidence: 99%

Scrambled Encryption Approach for Color Images Based on 9-D Chaotic Systems with 3-D Substitution Bit Levels

Abdel Hameed

2024

Aswan University Journal of Sciences and Technology

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Over the past few decades, the need for robust and secure communication has grown exponentially, particularly in image transmission over networks. This is due to the increasing reliance on digital technologies. This work demonstrates a novel "Scrambled Encryption Approach" that leverages the inherent unpredictability. To this end, nine-dimensional chaotic systems are combined with the innovative technique of 3-D substitution bit levels to verify strengths such as the confidentiality and integrity of visual data while maintaining fast encryption and decryption processes. This has the drawback of being vulnerable to known plaintext attacks and performing more sophisticated calculations than simpler encryption approaches. So, the proposed technique first separates the color input image into 24 bits to be categorized into 8 bits for each color channel (red, green, and blue). Then, 3-bit levels are used with position sequences for substitutions taken from the 9-D Lorenz chaotic system. After that, a multilayer differentiation technique produces three key matrices, which are then used to diffuse the scrambled components and produce the color cipher image. The simulation results show that our method has a high visual quality of decrypted images as well as high protection against brute force attacks because we have a large key space used for encryption data. Moreover, our proposed technique achieves more security against statistical attacks, including histogram analysis, information entropy, and correlation coefficients between pixels. Finally, the proposed encryption technique achieves a more secure transmission than state-of-the-art encryption approaches to guarantee integrity, privacy, and efficiency through global networks.

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Section: Introductionmentioning

confidence: 99%

Scrambled Encryption Approach for Color Images Based on 9-D Chaotic Systems with 3-D Substitution Bit Levels

Abdel Hameed

2024

Aswan University Journal of Sciences and Technology

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“…Digital multimedia steganography is an essential branch of information hiding, which provides a practical and secure way to address the problem of multimedia communication security. Steganography aims to hide messages in digital media such as images, audio, video, and text [2].…”

Section: Introductionmentioning

confidence: 99%

Preprocessing Strategy to Improve the Performance of Convolutional Neural Networks Applied to Steganalysis in the Spatial Domain

Bravo-Ortiz,

Mercado-Ruiz,

Villa-Pulgarin

et al. 2024

JAIT

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Recent research has shown that deep learning techniques outperform traditional steganography and steganalysis methods. As a result, researchers have proposed increasingly complex and more extensive convolutional Neural Networks (CNNs) to detect Steganographic images to achieve a 1%-2% improvement over the state-of-the-art. In this paper, we propose a data preprocessing and distribution strategy that enhances accuracy and convergence during training. Our method involves bifurcating Spatial Rich Model (SRM) and Discrete Cosine Transform (DCT) filters, with one branch being trainable and the other untrainable. This strategy is followed by three blocks of residual convolutions and an excitation layer. Our proposed method improves the accuracy of CNNs applied to steganalysis by 2%-15% while maintaining stability.

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“…Steganography has become one the most popular methods for information hiding because of its simplicity and easy communication through already existing technology and communication channels like IP cameras, smartphones, and social media apps like WeChat, WhatsApp, Telegram, Signal, etc. without any extra cost of additional infrastructures like private key sharing or private communication channels, etc. There have been various works which have not included deep learning in their work, however, have contributed in the field of watermarking and steganography (Hassaballah et al, 2020;Gutub and Al-Ghamdi, 2020;Gutub and Al-Roithy, 2021;Hassan and Gutub, 2021;Al-Roithy and Gutub, 2021;AlKhodaidi and Gutub, 2021;Hameed, Abdel-Aleem and Hassaballah, 2022;Gutub, 2022aGutub, , 2022b.…”

Section: Introductionmentioning

confidence: 99%

Latest Trends in Deep Learning Techniques for Image Steganography

Kumar

Sharma

Kumar

et al. 2023

International Journal of Digital Crime and Forensics

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The development of deep convolutional neural networks has been largely responsible for the significant strides forward made in steganography over the past decade. In the field of image steganography, generative adversarial networks (GAN) are becoming increasingly popular. This study describes current development in image steganographic systems based on deep learning. The authors' goal is to lay out the various works that have been done in image steganography using deep learning techniques and provide some notes on the various methods. This study proposed a result that could open up some new avenues for future research in deep learning based on image steganographic methods. These new avenues could be explored in the future. Moreover, the pros and cons of current methods are laid out with several promising directions to define problems that researchers can work on in future research avenues.

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A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques

Cited by 27 publications

References 58 publications

Scrambled Encryption Approach for Color Images Based on 9-D Chaotic Systems with 3-D Substitution Bit Levels

Scrambled Encryption Approach for Color Images Based on 9-D Chaotic Systems with 3-D Substitution Bit Levels

Preprocessing Strategy to Improve the Performance of Convolutional Neural Networks Applied to Steganalysis in the Spatial Domain

Latest Trends in Deep Learning Techniques for Image Steganography

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