Deep Residual Neural Networks for Image in Audio Steganography (Workshop Paper)

Agarwal, Shivam; Venkatraman, Siddarth

doi:10.1109/bigmm50055.2020.00071

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…In practice, we typically take into account a sender with a payload restriction, as illustrated in (3) that reduces the average distortion for a specified embedding rate R. Given that X and Y are combined finite alphabet groups and that x X=0, 1, m-1 and y Y=0, 1..., n-1, the distortion metric d (x, y) is best characterized by a distortion matrix shown as in (4), In order to accomplish peak signal-to-noise ratio that is high PSNR. The current colour RDH approaches [18], [23] for this color-marked image focus mostly on the relationships between the three colour channels. This implies that the three colour channels can be changed and the image quality will not be affected.…”

Section: Proposed Methodsmentioning

confidence: 99%

Colour image steganography through channel transformation approach

Neginal

Fatima²

2023

IJ-AI

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The interest in information security strategies is expanding due the quick expansion in the use of media content and transmission over the web employments. Accordingly, there is a need of special embedding procedure for steganography. The creator presents an original reversible data hiding (RDH) algorithm for colour pictures that further develops the inserting execution by applying a channel transformation function and a versatile expectation blunder extension prediction error expansion structure. The proposed calculation will bring the first colour picture with no information misfortune from the inserted picture (which is unique in addition to target picture). The evaluation is done here at the zero for the given base place for the histogram that marginally changes the pixel esteems for inserting the information. It can insert more information when contrasted with the majority of the current data hiding calculations. A hypothetical confirmation and various examinations state that the embedding capability of the proposed model which consistently is further noteworthy in comparison with other reversible data hiding techniques. The calculation has been applied to a wide scope of various colour pictures effectively. Some exploratory outcomes are introduced to show the legitimacy of the calculation.

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Section: Proposed Methodsmentioning

confidence: 99%

Colour image steganography through channel transformation approach

Neginal

Fatima²

2023

IJ-AI

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RETRACTED ARTICLE: Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach

Rao¹,

Jayasree²,

Rao³

2021

Soft Comput

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In the last two decades, it has been observed that there have been remarkable advancements in digital media communication. It has lots of advantages and business potential as it needs no physical media or transport. However, digital media can also create several big problems for media owners due to unauthorized use, ease of replication, plasticity, and equivalence of works in digital form. The possible solution is to secure digital media by cover writing which can also referred as steganography. Therefore, this article focusing on development of hybrid speech steganography system using spread spectrum-based redundant discrete wavelet transform (SS-RDWT). In general, speech steganography utilizes cover speech to embed the secrete message, however, the cover speech might be larger in size and contains many pauses, which requires more storage capacity, higher computational time, and even higher power usage results in system performance degradation. Hence, in addition to the proposed SS-RDWT approach, an intelligent pause detection protocol (IPDP) with maximum likelihood estimation (MLE) technique is employed for removing pause from cover speech signal, which reduces the transmission bandwidth, storage capacity and power consumption as well. Simulation results demonstrate that proposed hybrid steganography using integrated SS-RDWT with IPDP-MLE approach obtained superior performance as compared to state-of-art approaches.

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