Finding optimal least-significant-bit substitution in image hiding by dynamic programming strategy

Chang, Chin Chen; Hsiao, Ju-Yuan; Chan, Chi Shiang

doi:10.1016/s0031-3203(02)00289-3

Cited by 305 publications

(152 citation statements)

References 8 publications

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“…Among the cited cover media, digital images are preferred due to their high frequency over the internet [6]. The image in which the secret data has to be hidden is called the cover image [7] while the image containing the secret data is refers as stego-image (see Figure 2). …”

Section: Introductionmentioning

confidence: 99%

Robust Steganography based on Matching Pixel Locations

Halidou¹,

Mohamadou²,

Olle³

2017

IJCA

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Steganography consist of concealing secret information in a cover object to be sent over a public communication channel. It allows two parties to share hidden information in a way that no intruder can detect the presence of hidden information. This paper presents a novel steganography approach based on pixel location matching of the same cover image. Here the information is not directly embedded within the cover image but a sequence of 4 bits of secret data is compared to the 4 most significant bits (4MSB) of the cover image pixels. The locations of the matching pixels are taken to substitute the 2 least significant bits (2LSB) of the cover image pixels. Since the data are not directly hidden in cover image, the proposed approach is more secure and difficult to break. Intruders cannot intercept it by using common LSB techniques.

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Section: Introductionmentioning

confidence: 99%

Robust Steganography based on Matching Pixel Locations

Halidou¹,

Mohamadou²,

Olle³

2017

IJCA

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“…The initial work on LSB steganography was on LSB Substitution and was explored by (Chang et al, 2002), (THIEN et al, 2003), (Wang et al, 2000(Wang et al, , 2001, (Chang et al, 2003(Chang et al, , 2006 and (Chan et al, 2001(Chan et al, , 2004, which substitutes the same number of bits of each and every pixel of input host images for hiding the secret text or message and give rise to PoVs. They are easily attacked by the Chi-square Test given by (West fled et al, 1999), (Provos et al, 2002) and (Stanley, 2005).…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Information Security using an Improved Steganography Technique

Juneja¹,

Sandhu²

2013

Journal of Information Processing Systems

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Abstract-This research paper proposes a secured, robust approach of information security using steganography. It presents two component based LSB (Least Significant Bit) steganography methods for embedding secret data in the least significant bits of blue components and partial green components of random pixel locations in the edges of images. An adaptive LSB based steganography is proposed for embedding data based on the data available in MSB's (Most Significant Bits) of red, green, and blue components of randomly selected pixels across smooth areas. A hybrid feature detection filter is also proposed that performs better to predict edge areas even in noisy conditions. AES (Advanced Encryption Standard) and random pixel embedding is incorporated to provide two-tier security. The experimental results of the proposed approach are better in terms of PSNR and capacity. The comparison analysis of output results with other existing techniques is giving the proposed approach an edge over others. It has been thoroughly tested for various steganalysis attacks like visual analysis, histogram analysis, chi-square, and RS analysis and could sustain all these attacks very well.

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“…In spatial domain, the secret message is embedded into cover by using direct replacing of least significant bits of cover with the bits of secret message. For example, the methods presented in [3] [4] are stated in this group. The main advantage of spatial steganography to transformation domain steganography is high capacity.…”

Section: Introductionmentioning

confidence: 99%

Secure Information Transmission using Steganography and Morphological Associative Memory

Nazari¹,

Eftekhari²,

Moin³

2013

IJCA

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This paper presents a new steganography algorithm based on Morphology associative memory. Often, steganalysis methods are created to detect steganography algorithms using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). In this paper, cover images are mapped to morphological representation by using morphology transform containing morphological coefficients, and each bit of secret message is inserted in the least significant bit of morphological coefficients. To evaluate stego quality, we measure the quality of the cover image after embedding by comparing with other image transformed steganography algorithms such as discrete cosine and Wavelet transforms. The quality of stego has considerably improved in comparison with the state-of-art methods. In the other experimentation, we test the robustness of our proposed method by using Wavelet and Block-based steganalysis methods. The results show a high level of robustness of our algorithm respect to other steganography algorithms.

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Finding optimal least-significant-bit substitution in image hiding by dynamic programming strategy

Cited by 305 publications

References 8 publications

Robust Steganography based on Matching Pixel Locations

Robust Steganography based on Matching Pixel Locations

A New Approach for Information Security using an Improved Steganography Technique

Secure Information Transmission using Steganography and Morphological Associative Memory

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