An adaptive LSB matching steganography based on octonary complexity measure

Sabeti, Vajiheh; Samavi, Shadrokh; Shirani, Shahram

doi:10.1007/s11042-011-0975-y

Cited by 23 publications

(23 citation statements)

References 13 publications

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“…In [18], the authors proposed LSB-M adaptive steganography algorithm called Complexity Based LSB-M (CBL). They used an 8-neighborhood of a pixel to determine the complexity region for embedding data in that region.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed algorithm uses both LSB-M and LSB replacement to address these criteria. An adaptive algorithm that is a modification to CBL approach [18] is proposed. Details of embedding and extraction phases are presented in the next lines.…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…This image will be used to compute the complexity values of pixels in the next step. Using the secondary image helps the receiver to get the same complexity value [18]. The following routine creates this image.…”

Section: A Embedding Phasementioning

confidence: 99%

“…Image steganographic algorithms can be classified in terms of the embedding domain into two main classes: spatial domain and frequency domain-based algorithms [17], [18]. Spatial domain-based algorithms conceal secret message straightforwardly in the intensity of pixels of an image, while in frequency domain-based algorithms, the image is firstly transformed into its frequency domain and secret message is then concealed in the transform coefficients [19], [20].…”

Section: Introductionmentioning

confidence: 99%

“…In [18], the authors proposed a method called Complexity Based LSB-M (CBL). The method employs the strategy of adaptivity and the use of LSB-M in order to increase the security against attacks.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Hybrid Steganography System based on LSB Matching and Replacement

Hiary¹,

Sabri²,

Mohammed³

et al. 2016

ijacsa

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Abstract-This paper proposes a hybrid steganographic approach using the least significant bit (LSB) technique for grayscale images. The proposed approach uses both LSB matching (LSB-M) and LSB replacement to hide the secret data in images. Using hybrid LSB techniques increase the level of security. Thus, attackers cannot easily, if not impossible, extract the secret data. The proposed approach stores two bits in a pixel. The embedding rate can reach up to 1.6 bit per pixel. The proposed approach is evaluated and subjected to various kinds of image processing attacks. The performance of the proposed algorithm is compared with two other relevant techniques; pixelvalue differencing (PVD) and Complexity Based LSB-M (CBL). Experimental results indicate that the proposed algorithm outperforms PVD in terms of imperceptibility. Also, it significantly outperforms CBL in two main features; higher embedding rate (ER), and more robust to most common image processing attacks such as median filtering, histogram equalization, and rotation.

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Section: Related Workmentioning

confidence: 99%

Section: Proposed Algorithmmentioning

confidence: 99%

Section: A Embedding Phasementioning

confidence: 99%