Data hiding in digital images using a partial optimization technique based on the classical LSB method

Akar, Feyzi; Yalman, Yildiray; Varol, H. Selçuk

doi:10.3906/elk-1205-58

Cited by 6 publications

(6 citation statements)

References 12 publications

(12 reference statements)

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“…Least significant bits of each byte of the cover object are replaced with secret message bits in this technique [8]. For example, the letter "a" ((97) ASCII = (01100001) 2 ) can be easily hidden inside eight bytes of a cover data as seen in Table 1.…”

Section: Lsb Coding Techniquementioning

confidence: 99%

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Visual steganalysis of LSB-encoded audio data based on frequency domain characteristics

Arslan

Yalman

2013

Proceedings of the 6th International Conference on Security of Information and Networks

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Steganography is an art and science of information hiding. Text, audio and image files are usually used as cover data. Then, a secret message is embedded into these cover data that no one knows about it except sender and receiver. Mostly used methods for audio steganography are based on Least Significant Bit (LSB) method and its derivatives in the literature. Steganalysis is a methodology of detecting messages hidden using steganography. In this paper, a visual steganalysis method has been proposed. Secret text messages can be detected by using frequency domain characteristics of stego audio data which contain text messages. Experimental results show that if stego object contains text messages and it is encoded by LSB or its varieties, some remarkable changes can be observed in frequency domain characteristics and its spectrogram. Thanks to exploring these frequency domain characteristics of stego objects, steganalysis (stego text detection) on audio data can be visually realized.

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Section: Lsb Coding Techniquementioning

confidence: 99%

“…The goal of steganalysis is to identify suspected data determine whether or not they have a payload encoded into them, and, if possible, recover that payload [8][9][10][11]. In this paper, a visual steganalysis technique has been proposed for LSB-encoded audio data based on frequency domain characteristics.…”

Section: Introductionmentioning

confidence: 99%

Visual steganalysis of LSB-encoded audio data based on frequency domain characteristics

Arslan

Yalman

2013

Proceedings of the 6th International Conference on Security of Information and Networks

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“…Furthermore, as the proposed method is tested on images of Lena, Tiffany, House, Pepper, Baboon, Jet, and Lake, the PSNR value for 32 KB is 53.52-53.55 dB, while it is 51.12-51.15 dB for the LSBR method. Table 5 shows the performances of the proposed method as well as the other 7 methods [7,[25][26][27][28][29][30], which have been developed in recent years. Several images, sizes, and payloads units of the available literature have been used.…”

Section: Image Quality Performance Of the Stego Imagementioning

confidence: 99%

“…In steganography, the objects used for hiding the secret data are called cover objects, which can be text, image, video, sound data, etc. The combination of the cover object and the secret data hidden by it is called the stego object, which may appear as an ordinary text, image, video, or sound data [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A new efficient block matching data hiding method based on scanning order selection in medical images

Aydoğan¹,

Bayılmış²

2017

Turk J Elec Eng & Comp Sci

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Digital technology and the widespread use of the Internet has increased the speeds at which digital data can be obtained and shared in daily life. In parallel to this, there are important concerns regarding the confidentiality of private data during data transmissions and the possibility that data might fall into the hands of third parties. Issues relating to data safety can also affect patients' medical images and other information relating to these images. In this study, we propose a new method based on block matching that can be used to hide the patient information in medical images. In this method, 8 scanning orders (6 of which are newly designed) are developed to provide high image quality.By diversifying the number of scanning orders, we aim to achieve the lowest number of bit changes. The performance of the developed method is measured using the number of bits subject to change, the peak signal-to-noise ratio and the mean structural similarity index measure image quality assessment metrics, and steganalysis attacks. The method we developed was found to be more effective in hiding data compared to the classical least significant bit method.

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“…In the spatial domain, the watermark is embedded by modifying the pixel values in the original image. The simplest spatial domain watermarking technique is to embed the bits of the message directly into the least * Correspondence: onur.jane@tubitak.gov.tr significant bit plane of the cover image [3]. Transform domain watermarking is similar to spatial domain watermarking; in this case, the coefficients of transforms such as discrete cosine transform (DCT), discrete Fourier transform (DFT), or discrete wavelet transform (DWT) are modified [4].…”

Section: Introductionmentioning

confidence: 99%

A new approach of nonblind watermarking methods based on DWT and SVD via LU decomposition

Jane¹,

Elbaşi²

2014

Turk J Elec Eng & Comp Sci

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Multimedia security has been the focal point of considerable research activity in the last decade, mainly because of its wide application area. Watermarking, in particular, is identified as a major technology to achieve copyright protection and multimedia security. Therefore, recent studies in the literature include some evident approaches for embedding data into a multimedia element. Because of its useful frequency component separation, the discrete wavelet transform (DWT) is commonly used in watermarking schemes. Moreover, singular value decomposition (SVD) and lower-and-upper (LU) decomposition have little effect on the perception of the watermark. Therefore, in this study, a combination of DWT and SVD via LU decomposition is proposed as a new nonblind watermarking algorithm that requires cover work to detect the watermark. Experimental results show that the proposed algorithm is considerably robust and reliable against certain attacks without degrading the input image, by embedding a binary watermark on the low-low band. Moreover, the threshold values are data-dependent for watermarks after attacks; that is, the threshold value is always different from another for certain attacks so that similarity ratios in this algorithm, as a quality metric, are much more than those of the other algorithms consisting of DWT and/or SVD despite strong attacks causing lower peak signal-to-noise ratio values. Apart from robustness, reliability, and data-dependence, the other novel aspect of this study is to expand the application areas of watermarking with a new algorithm consisting of DWT, LU, and SVD, and this study will contribute to the literature for certain cases.

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Data hiding in digital images using a partial optimization technique based on the classical LSB method

Cited by 6 publications

References 12 publications

Visual steganalysis of LSB-encoded audio data based on frequency domain characteristics

Visual steganalysis of LSB-encoded audio data based on frequency domain characteristics

A new efficient block matching data hiding method based on scanning order selection in medical images

A new approach of nonblind watermarking methods based on DWT and SVD via LU decomposition

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