Chaotic system-based secure data hiding scheme with high embedding capacity

Yadav, Gyan Singh; Ojha, Aparajita

doi:10.1016/j.compeleceng.2018.02.022

Cited by 12 publications

(10 citation statements)

References 14 publications

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“…Keeping this in mind several schemes based on secret keys have been proposed in recent years [16]. Recently, Yadav and Ojha [17] proposed a more efficient scheme to embed the secret data into random locations of the image through chaotic systems for security, which provides a higher payload and imperceptibility.…”

Section: Introductionmentioning

confidence: 99%

An efficient and adaptive data-hiding scheme based on secure random matrix

Zhang

Harn

2019

PLoS ONE

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There is a vivid research on securely deliver a secret message by using a data hiding technique in digital images. However, most existing solutions of data-hiding need to encrypt secret data first, and embed the encrypt message into cover image, which is not promising any security once the embedding algorithm is leaked. In this paper, an efficient and adaptive data hiding scheme is presented which is based on a new reference matrix named secure reference matrix. The scheme is flexible enough to meet different data hiding capacities and image quality as needed, and we allow the reference matrix to be more secure since it is randomly generated each time and make it much harder for being attack with exhaustive manner by extending the possible solution. We give the detail protocol for our scheme and provide the practical test and performance analysis. Experimental results show that our scheme has a better flexibility and efficiency in embedding process, and the average value of Peak Signal to Noise Ratio (PSNR) for the stego-images which are generated by our scheme have a higher visual quality for different embedding capacities, and our scheme is more efficient compared with related work.

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Section: Introductionmentioning

confidence: 99%

An efficient and adaptive data-hiding scheme based on secure random matrix

Zhang

Harn

2019

PLoS ONE

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“…According to (5), we generated a series of discrete chaotic sequences with different computational precision, including = 8, 12, 16, and 24. In order to test the effect of computation precision on discrete chaotic sequences, we performed autocorrelation test, permutation entropy test, and statistical analysis of sequence periodicity for the above chaotic sequences.…”

Section: Influence Of Computational Precision Onmentioning

confidence: 99%

“…Therefore, in recent years, chaos theory has been widely applied in the field of cryptography and secret communication [1][2][3][4]. For instance, Yadav et al [5] proposed a chaotic system-based data hiding scheme that provides high payload and imperceptibility. Murillo-Escobar et al [6] put forward a novel pseudorandom number generator based on pseudorandomly enhanced Logistic map.…”

Section: Introductionmentioning

confidence: 99%

Effects of Limited Computational Precision on the Discrete Chaotic Sequences and the Design of Related Solutions

Fan

Ding

2019

Complexity

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In this paper, we analyzed the periodicity of discrete Logistic and Tent sequences with different computational precision in detail. Further, we found that the process of iterations of the Logistic and Tent mapping is composed of transient and periodic stages. Surprisingly, for the different initial iterative values, we first discovered that all periodic stages have the same periodic limit cycles. This phenomenon has seriously affected the security of chaotic cipher. To solve this problem, we designed a novel discrete chaotic sequence generator based on m-sequence and discrete chaotic mapping. The experimental results indicated that the chaotic sequence generator can generate pseudorandom chaotic sequences with large periodicity and good performance under the condition of limited computational precision.

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“…The success of steganography lies in transmission of stego objects without suspicion [1]. A large number of image steganographic techniques have appeared in the literature, for example [2][3][4][5][6][7]. These techniques can be classified into two main classes: spatial domain and transform domain techniques.…”

Section: Introductionmentioning

confidence: 99%

“…These techniques can be classified into two main classes: spatial domain and transform domain techniques. In spatial domain techniques, private message is embedded in the intensity of image pixels directly [2][3][4]. In transform domain techniques, the private message is embedded in the cover by modifying coefficients in a transform domain such as discrete cosine transform (DCT) and integer discrete wavelet transform [5][6].…”

Section: Introductionmentioning

confidence: 99%

Combined Image Encryption And Steganography Algorithm In The Spatial Domain

Abdelgader

Aboughalia

Alkishriwo

2018

Proceedings of First Conference for Engineering Sciences and Technology: Vol. 1

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A B S T R A C TIn recent years, steganography has emerged as one of the main research areas in information security. Least significant bit (LSB) steganography is one of the fundamental and conventional spatial domain methods, which is capable of hiding larger secret information in a cover image without noticeable visual distortions. In this paper, a combined algorithm based on LSB steganography and chaotic encryption is proposed. Experimental results show the feasibility of the proposed method. In comparison with existing steganographic spatial domain based algorithms, the suggested algorithm is shown to have some advantages over existing ones, namely, larger key space and a higher level of security against some existing attacks.

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Chaotic system-based secure data hiding scheme with high embedding capacity

Cited by 12 publications

References 14 publications

An efficient and adaptive data-hiding scheme based on secure random matrix

An efficient and adaptive data-hiding scheme based on secure random matrix

Effects of Limited Computational Precision on the Discrete Chaotic Sequences and the Design of Related Solutions

Combined Image Encryption And Steganography Algorithm In The Spatial Domain

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