Cover selection steganography with intra-image scanning

Hajduk, Vladimir; Levický, Dušan

doi:10.1109/radioelek.2018.8376370

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…The amount of applications for image encryption algorithms is still rising. Probably the most obvious one is usage of encryption prior to information hiding via steganography [14,15]. The image encryption algorithms could be also used for modification of image data into a set of samples with more uniform distribution, which could be helpful for some processing operations [16].…”

Section: Discussionmentioning

confidence: 99%

An Image Encryption Algorithm with Total Diffusion

Oravec

Turán

Ovseník

2018

Carpathian Journal of Electronic and Computer Engineering

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This paper proposes an image encryption algorithm which uses four scans of an image during the diffusion stage in order to achieve total diffusion between intensities of image pixels. The condition of total diffusion is fulfilled by a suitable combination of techniques of ciphertext chaining and plaintext related diffusion. The proposed encryption algorithm uses two stages which utilize chaotic logistic map for generation of pseudo-random sequences. The paper also briefly analyzes approaches described by other researchers and evaluates experimental results of the proposed solution by means of commonly used measures. Properties of our proposal regarding modifications of plain images prior to encryption or modifications of encrypted images prior to decryption are illustrated by two additional experiments. The obtained numeric results are compared with those achieved by other proposals and briefly discussed.

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Section: Discussionmentioning

confidence: 99%

An Image Encryption Algorithm with Total Diffusion

Oravec

Turán

Ovseník

2018

Carpathian Journal of Electronic and Computer Engineering

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“…Considering these advantages, MOEA is also used in steganography to optimise features, either capacity, imperceptibility, or robustness. For instance, a recent study by Hajduk and Levický (2018) combined both MOEA and steganography for image steganography and implemented NSGA to optimise the stego file. The study proposed a new method of embedding a secret message within the discrete wavelet transform using singular value decomposition (SVD) and NSGA.…”

Section: Moeamentioning

confidence: 99%

“…However, the result may not always be good since it depends on the cover file and the secret message (Shah & Bichkar, 2020). The main idea is to find the optimal cover file from its database using a specific search method for the specific secret message (Hajduk & Levický, 2018). If the criterion of a good cover file is met based on comparison parameters, the relevant cover file will be used as a carrier for the secret message.…”

Section: Cover Selectionmentioning

confidence: 99%

“…If the criterion of a good cover file is met based on comparison parameters, the relevant cover file will be used as a carrier for the secret message. For image steganography, many studies have been introduced for cover image selection (Abdul Sattar & Talib Gaata, 2017;Hajduk & Levický, 2018;Sajedi & Jamzad, 2008;Shah & Bichkar, 2020;Wang et al, 2020;Wang & Zhang, 2019). The same goes for cover video selection in video steganography .…”

Section: Cover Selectionmentioning

confidence: 99%

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Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm

Azam¹,

Ridzuan²,

Sayuti³

2023

Journal of Information and Communication Technology

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Existing embedding techniques depend on cover audio selected by users. Unknowingly, users may make a poor cover audio selectionthat is not optimised in its capacity or imperceptibility features, which could reduce the effectiveness of any embedding technique. As a trade-off exists between capacity and imperceptibility, producing a method focused on optimising both features is crucial. One ofthe search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. The proposed method provided suggestions for cover audio to users based on imperceptibility and capacity features. The sample difference calculation was initially formulated to determine the maximum capacity for each cover audio defined in the cover audio database. Next, NSGA-II was implemented to determine the optimised solutions based on the parameters provided by each chromosome. The experimental results demonstrated the effectiveness of the proposed method as it managed to dominate thesolutions from the previous method selected based on one criterion only. In addition, the proposed method considered that the trade-off managed to select the solution as the highest priority compared to the previous method, which put the same solution as low as 71 in the priority ranking. In conclusion, the method optimised the cover audio selected, thus, improving the effectiveness of the audio steganography used. It can be a response to help people whose computers and mobile devices continue to be unfamiliar with audio steganography in an age where information security is crucial.

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Steganography in TCP/IP Networks

Tymchenko

Havrysh

2023

Advances in Artificial Systems for Medicine and Education VI

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Cover selection steganography with intra-image scanning

Cited by 3 publications

References 13 publications

An Image Encryption Algorithm with Total Diffusion

An Image Encryption Algorithm with Total Diffusion

Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm

Steganography in TCP/IP Networks

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