A High-Capacity Image Steganography Method Using Chaotic Particle Swarm Optimization

Pretext & Motivations: Spatial domain-based image steganography is the stowing away technique in which disguised data is hidden directly inside the pixel intensities of an unclassified image. After a systematic literature review based on the PRISMA framework, it was realized that no single disquisition has covered all three acreages together i.e., improved payload capacity, augmented security, and reduced image degradation. Chaotic method was restricted to be used as fodder for searching techniques or diffusion of disguised data within the CI. In the proffered approach, a novel use of chaotic function as bombs that can be used to guard the real message is explored. Proffered Method: The proffered method can be divided into two parts: Insertion of secret text (Huffman compression + novel M-Log chaos bombs embedding + d-Hybrid 3-LSB) and extracting the recondite message out (diffusing chaos bombs + decompressing the message). Results: Efficient developments were achieved by the proffered method in all three acreages i.e., Payload improvement of 40%, mean PSNR of 45.8981 and mean SSIM of 0.9931, and 32% image degradation reduction. Conclusion and Future Scope: The proposed method used Huffman compression to clinch the up-scaled payload. Chaotic function values, along with a modulus function, were used to feed into a novel bomb generator equation [ ], which fosters locus for stashing chaos bombs in any image. When triggered by the attacker, these bombs caused permanent marring of recondite data, denying the intruder access to disguised information. As an additional element, image degradation caused was reduced by the pristine d-hybrid method. For future studies, the use of multidimensional chaotic functions and different searching techniques for identifying ideal locations for stashing chaos bombs can be explored.

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“…Logistic map: Logistic equation is, x n+1 = rx n (1 − x n ) where r is the catalyst of chaos. The logistic map is elucidated in figure [6].…”

Section: Figure 4: Non-linear Characteristic Of Chaosmentioning

confidence: 99%

“…Step 2: If PVD belongs to [6,7] ADD DECI 8 in the stego pixel intensity without altering the embedded LSBs…”

Section: Step 3: Reducing Image Degradationmentioning

confidence: 99%

A Novel M-Log Chaos Method for Enhanced Security Blended with Pristine d-Hybrid LSB Approach for Reducing Image Degradation Hinged on Huffman Compression of English Text for Payload Improvement

Raghuvanshi

Joshi

Nandal

et al. 2023

Preprint

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“…However, one disadvantage of using PSO is that the particles become subject to early convergence, resulting in the swarm being trapped in an ideal local region and the inability to locate any new area within the local optimal solution. As a result, access to the global optimal solution becomes limited [19]. Therefore, in this study, we customized the PSO algorithm (as given in Eq.…”

Section: Psomentioning

confidence: 99%

“…As a result, access to the global optimal solution becomes limited. Therefore, Jaradat et al [19] employed logistic chaotic map with PSO to solve this problem and presented its application to image steganography, in which the role of PSO is to locate the effective pixel position in the carrier image to conceal the secret data.…”

Section: Introductionmentioning

confidence: 99%

A robust medical image steganography approach based on particle swarm optimization algorithm and quantum walks

Abd-El-Atty¹

2022

Neural Comput & Applic

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Medical information plays an essential task in our everyday lives, in which medical data privacy and security constitute an important issue. The confidentiality of medical data can be achieved by applying one or more encryption and data hiding methods. Amidst the development of quantum computers, most medical data confidentiality techniques may be hacked because their construction is based on mathematical models. Most medical data have a long lifetime exceeding 25 years. Therefore, it is an important issue to design a new medical data hiding technique that has the capability to withstand the probable attacks from the side of quantum or digital devices. In this article, we aim to present a novel medical image steganography strategy based on quantum walks, chaotic systems, and particle swarm optimization algorithm. A 3-D chaotic system and quantum walks are utilized for operating particle swarm optimization algorithm, in which the generated velocity sequence is utilized for substituting the confidential data, and the position sequence is utilized for selecting which position in the hosting image will be employed to host the substituted confidential data. The payload capacity of the suggested mechanism is 2 bits per 1 byte, and the average value for PSNR is 44.1, which is big enough for the naked eye to not differentiate the difference between the carrier image and its stego one.

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“…Searching for the best parameter is the mission of GA in order to find or achieve high quality for masking images. Aya Jaradat et al [13] built a steganography system based on hide confidential information in the best locations of image by using swarm optimization method and chaos theory. The goal of dividing the image into blocks is to improve steganography capacity so each block stores a number of secret bits.…”

Section: -0652mentioning

confidence: 99%

Review on Common Steganography Techniques

Ayoob

Hussein

2022

JUBPAS

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Various authorities are keen to preserve the confidentiality of their information and protect it from competing or hostile parties who were also keen to access that information by all available means. Since the encryption of information is exposed as it produces incomprehensible texts that arouse suspicion, some tend to work in a way that removes suspicions by hiding the information in a medium like text or picture so that what is sent and circulated appears natural and free of signs or incomprehensible symbols as if not loaded with any additional information. This paper introduces a review the techniques used to hide data in images as one of the most common concealment techniques.

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A High-Capacity Image Steganography Method Using Chaotic Particle Swarm Optimization

Cited by 27 publications

References 25 publications

A Novel M-Log Chaos Method for Enhanced Security Blended with Pristine d-Hybrid LSB Approach for Reducing Image Degradation Hinged on Huffman Compression of English Text for Payload Improvement

A Novel M-Log Chaos Method for Enhanced Security Blended with Pristine d-Hybrid LSB Approach for Reducing Image Degradation Hinged on Huffman Compression of English Text for Payload Improvement

A robust medical image steganography approach based on particle swarm optimization algorithm and quantum walks

Review on Common Steganography Techniques

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