Cover image selection for embedding based on different criteria

Rashid, Rasber

doi:10.1117/12.2560720

Cited by 2 publications

(3 citation statements)

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“…This analysis aimed to determine the best selection criteria based on the solutions selected. The nearest implementation of the cover selection method, which covered several characteristics during the selection process, was the method by Rashid (2020). However, since this method focused on the image cover selection, a direct comparison was impossible as the metric used was unsuitable for audio.…”

Section: Comparison Analysis Between the Selection Criteriamentioning

confidence: 99%

“…Therefore, for the comparison purpose, three selection criteria were considered in this analysis: 1) SNR and 𝑑𝑑𝑑𝑑𝑑𝑑 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 , 2) SNR only, and 3) 𝑑𝑑𝑑𝑑𝑑𝑑 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 only. Two selection criteria, SNR only and 𝑑𝑑𝑑𝑑𝑑𝑑 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 only, focused on one characteristic method by Rashid (2020), which assessed based on different criteria separately. Meanwhile, SNR and 𝑑𝑑𝑑𝑑𝑑𝑑 𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 represented the proposed method that evaluated each criterion simultaneously.…”

Section: Comparison Analysis Between the Selection Criteriamentioning

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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Section: Comparison Analysis Between the Selection Criteriamentioning

confidence: 99%

Section: Comparison Analysis Between the Selection Criteriamentioning

confidence: 99%

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

Azam¹,

Ridzuan²,

Sayuti³

2023

Journal of Information and Communication Technology

View full text Add to dashboard Cite

show abstract

“…Then both percentage values are compared and the cover image that has the most similar percentage value of '1' with secret message are selected. [13] proposed cover selection that used four evaluation metrics which are PSNR, match bits, Different Image Histogram (DIH) and Revisited Weighted Stego (RWS). Then it produces four distinct ranking lists based on these four metrics.…”

Section: Introductionmentioning

confidence: 99%

A Method of Cover Audio Selection for Embedding Based on Various Criteria

Noor Azam,

Ridzuan,

Mohd Sayuti

et al. 2024

ITM Web Conf.

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The main goal of an audio steganography method is to improve the capacity, im-perceptibility, and robustness. Several methods of audio steganography have been proposed to enhance its capabilities. To further optimize the efficiency of the audio steganography method, this paper proposes to select the appropriate audio cover for concealing the message. The selection of an appropriate cover can significantly improve the quality of the output and facilitate the development of innovative audio steganography techniques. This paper proposed a new audio cover selection method, which can further enhance the characteristics of the resulting output. This method ranked each cover according to the qualities that need to be boosted using various measurements. These measurements are the Maximum Available Space (MAS), Peak Signal to Noise Ratio (PSNR) and Bit Error Rate (BER) for capacity, imperceptibility, and robustness respectively. Based on the experiment conducted using five cover audios stored in the self-created database, each audio is ranked differently based on the measurement used to determine its characteristic level. In conclusion, the proposed cover selection method can be used to select the most proper cover, hence improving the characteristics of audio steganography.

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Cover image selection for embedding based on different criteria

Cited by 2 publications

References 0 publications

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

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

A Method of Cover Audio Selection for Embedding Based on Various Criteria

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