A short survey on image steganography and steganalysis techniques

Chanu, Yambem Jina; Tuithung, Themrichon; Singh, Kh. Manglem

doi:10.1109/ncetacs.2012.6203297

Cited by 37 publications

(22 citation statements)

References 24 publications

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“…Some surveys on image steganography have highlighted different approaches [4][5][6][7][8][9]. Saha, et.…”

Section: Related Workmentioning

confidence: 99%

“…SSIM is defined as [29] : XY . 1 C and 2 C are constants with (5) After embedding full capacity secret messages in eighteen different cover images, the result of the stego-image for each cover image was produced and then MSEavg, PSNR, SSIM, BR values of the stego-images were calculated. Table 5, shows the comparison result of proposed algorithm between cover and stego image of eighteen 512*512 (24 bit color) size.…”

Section: Experimental Setting and Assessment Of Image Qualitymentioning

confidence: 99%

“…Discrete cosine transformation (DCT), fourier transformation (FT) and discrete wavelet transformation (DWT) are some techniques used for this purpose [4]. On the other hand, steganography in the image spatial domain generally uses a direct least significant bit (LSB) replacement technique -encoding at the level of the LSBs [5].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Variant of LSB Steganography Algorithm for Hiding Information in RGB Images

Mandal¹,

Kahar²

2017

IJSIP

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“…Some surveys on image steganography have highlighted different approaches [4][5][6][7][8][9]. Saha, et.…”

Section: Related Workmentioning

confidence: 99%

Section: Experimental Setting and Assessment Of Image Qualitymentioning

confidence: 99%

See 1 more Smart Citation

Variant of LSB Steganography Algorithm for Hiding Information in RGB Images

Mandal¹,

Kahar²

2017

IJSIP

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show abstract

“…[2,4] Encrypted messages can sometimes be broken by cryptanalysis, also called codebreaking, although modern cryptography techniques are virtually unbreakable. [6] In computer science and information theory, data compression, source coding, or bit-rate reduction involves encoding information using fewer bits than the original representation. [8] Compression can be either lossy or lossless.…”

Section: Introductionmentioning

confidence: 99%

Double Layer Image Security System using Encryption and Steganography

Brar¹,

Brar²

2016

IJCNIS

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The image security on internet transfers is the concern of the hour as the breaching attacks into the image databases are rising every year. The hackers take advantage of the stolen personal and important images to fulfill their dangerous and unethical intentions. The image data theft can be used to defame a person on the internet by posting the illegal and unacceptable images of that person (internet user). Hence the images transfers have to be secure to ensure the privacy of the user's image data. In this research, a number of image security systems have been studied to evaluate the research gap. Majority of the existing image security systems are not up to date to protect against the latest breaching attacks. So, we have proposed an effective and robust image security framework particularly designed for the images. The proposed has been designed and implemented using MATLAB. In this research, a hybrid image security framework has been proposed to overcome the problem stated earlier, which will be implemented by combining various techniques together to achieve the image security goal. The techniques included in the combination would beimage compression, cryptography and steganography. DWT compression has been used, because it is a stronger compression algorithm. The steganographed image would be compressed to reduce its size. Blowfish encryption algorithm would be used for the encryption purposes. It offers maximum throughput (faster) and also energy efficient. Compressed image would be encrypted to enhance the image security. Real image will be hidden into another image. A cluster based steganographic technique will be used. Real image and face image would be analyzed, and the real image would be embedded in those areas of face image, where color schemes of the real image and face image would be most similar. Kmeans or Hierarchical clustering would be used as a clustering technique. An all new comparative analysis technique would be applied to make the comparison between real image and base image on the basis of color patterns.

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“…Several lossy image compression methods have been proposed and discussed [5][6][7][8][9]. Most popular lossy compression method is JPEG [10], which is widely used for storing and communicating digital images over the internet.…”

Section: Introductionmentioning

confidence: 99%

A Novel Lossy Image Compression Method

Akhtar

Khan

Siddiqui

2014

2014 Fourth International Conference on Communication Systems and Network Technologies

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In this paper, we propose and implement a new lossy method to compress a digital image. We perform technique like quantization, smoothing before applying our novel, simple addition based technique to compress the image. The image is divided into set of 4*4 blocks. The results are good and comparable to JPEG compression algorithm, particularly when image quality is high. The compression ratio in the proposed method is high when adjacent pixel values in the image are close, which is usual in real images. (Abstract)

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A short survey on image steganography and steganalysis techniques

Cited by 37 publications

References 24 publications

Variant of LSB Steganography Algorithm for Hiding Information in RGB Images

Variant of LSB Steganography Algorithm for Hiding Information in RGB Images

Double Layer Image Security System using Encryption and Steganography

A Novel Lossy Image Compression Method

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