Genetic algorithms for optimality of data hiding in digital images

Maity, Santi P.; Kundu, Malay K.

doi:10.1007/s00500-008-0329-5

Cited by 24 publications

(5 citation statements)

References 17 publications

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“…The research issue became more oriented after that, with the goal of developing sophisticated, robust LSB-based cryptography-steganography that can withstand such steganalysis attacks (Patel and Meena, 2016;Rajendran and Doraipandian, 2017;Shafi et al, 2018). Learning methods, for example, were used to optimise LSB substitution (Maity and Kundu, 2009;Dadgostar and Afsari, 2016).…”

Section: Related Workmentioning

confidence: 99%

Fuzzy Proximity based Robust Data Hiding Scheme with Interval Threshold

Singh

Jana

Datta

2022

Preprint

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In 2020, Ashraf et al. proposed an interval type-2 fuzzy logic based block similarity calculation using color proximity relations of neighboring pixels in a steganographic scheme. Their method works well for detecting similarity, but it has drawbacks in terms of visual quality, imperceptibility, security, and robustness. Using Mamdani fuzzy logic to identify color proximity at the block level, as well as a shared secret key and post-processing system, this paper attempts to develop a robust data hiding scheme with similarity measure to ensure good visual quality, robustness, imperceptibility, and enhance the security. Further, the block color proximity is graded using an interval threshold. Accordingly, data embedding is processed in the sequence generated by the shared secret keys. In order to increase the quality and accuracy of the recovered secret message, the tampering coincidence problem is solved through a post-processing approach. The experimental analysis, steganalysis and comparisons clearly illustrate the effectiveness of the proposed scheme in terms of visual quality, structural similarity, recoverability and robustness.

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Section: Related Workmentioning

confidence: 99%

Fuzzy Proximity based Robust Data Hiding Scheme with Interval Threshold

Singh

Jana

Datta

2022

Preprint

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“… 2018 ). Learning methods, for example, were used to optimize LSB substitution (Maity and Kundu 2009 ; Dadgostar and Afsari 2016 ).…”

Section: Related Workmentioning

confidence: 99%

Fuzzy proximity-based robust data hiding scheme with interval threshold

2022

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Secret communication of sensitive data must progress in a trustworthy environment through data hiding. Using Mamdani fuzzy logic to identify color proximity at the block level and a shared secret key and post-processing system, this paper attempts to develop a robust data hiding scheme with similarity measures to ensure good visual quality, robustness, imperceptibility and enhance the security. In accordance with the Gestalt principle, proximity among the nearby objects is higher, whose value varies from expert to expert. Therefore, a possibility for type-I fuzzy logic to be used to evaluate proximity. Fuzzy proximity is computed by means of a difference in intensity (colordiff) and distance (closeness). Further, the block color proximity obtained from the proximity calculation network is graded using an interval threshold. Accordingly, data embedding is processed in the sequence generated by the shared secret keys. The tampering coincidence problem is solved through a post-processing approach to increase the quality and accuracy of the recovered secret message. The experimental analysis, steganalysis and comparisons clearly illustrate the effectiveness of the proposed scheme in terms of visual quality, structural similarity, recoverability and robustness.

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“…The difference lies in the usage of DWT for signal decomposition. We use two biorthogonal wavelet filters (6,8) and (4,4) for the experimentation, although other biorthogonal wavelets can also be used.…”

Section: Watermark Embeddingmentioning

confidence: 99%

Performance Improvement in Spread Spectrum Image Watermarking Using Wavelets

Maity

Kundu

2011

Int. J. Wavelets Multiresolut Inf. Process.

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This paper investigates the scope of wavelets for performance improvement in spread spectrum image watermarking. Performance of a digital image watermarking algorithm, in general, is determined by the visual invisibility of the hidden data (imperceptibility), reliability in the detection of the hidden information after various common and deliberate signal processing operations (robustness) applied on the watermarked signals and the amount of data to be hidden (payload) without affecting the imperceptibility and robustness properties. In this paper, we propose a few spread spectrum (SS) image watermarking schemes using discrete wavelet transform (DWT), biorthogonal DWT and M -band wavelets coupled with various modulation, multiplexing and signaling techniques. The performance of the watermarking methods are also reported along with the relative merits and demerits.

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Genetic algorithms for optimality of data hiding in digital images

Cited by 24 publications

References 17 publications

Fuzzy Proximity based Robust Data Hiding Scheme with Interval Threshold

Fuzzy Proximity based Robust Data Hiding Scheme with Interval Threshold

Fuzzy proximity-based robust data hiding scheme with interval threshold

Performance Improvement in Spread Spectrum Image Watermarking Using Wavelets

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