Medical JPEG image steganography method according to the distortion reduction criterion based on an imperialist competitive algorithm
01 Feb 2021-Iet Image Processing (The Institution of Engineering and Technology)-Vol. 15, Iss: 3, pp 705-714
About: This article is published in Iet Image Processing.The article was published on 2021-02-01 and is currently open access. It has received 3 citations till now. The article focuses on the topics: Imperialist competitive algorithm & Steganography.
Citations
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01 Jan 2013
TL;DR: In this article, the security requirements of medical images as well as expected threats in teleradiology are reviewed starting with various security and privacy standards, and the limitations of the conventional measures used against the expected threats.
Abstract: Teleradiology allows medical images to be transmitted over electronic networks for clinical interpretation, and for improved healthcare access, delivery and standards. Although, such remote transmission of the images is raising various new and complex legal and ethical issues, including image retention and fraud, privacy, malpractice liability, etc., considerations of the security measures used in teleradiology remain unchanged. Addressing this problem naturally warrants investigations on the security measures for their relative functional limitations and for the scope of considering them further. In this paper, starting with various security and privacy standards, the security requirements of medical images as well as expected threats in teleradiology are reviewed. This will make it possible to determine the limitations of the conventional measures used against the expected threats. Further, we thoroughly study the utilization of digital watermarking for teleradiology. Following the key attributes and roles of various watermarking parameters, justification for watermarking over conventional security measures is made in terms of their various objectives, properties, and requirements. We also outline the main objectives of medical image watermarking for teleradiology, and provide recommendations on suitable watermarking techniques and their characterization. Finally, concluding remarks and directions for future research are presented.
6 citations
Journal Article•
TL;DR: In this article, a technique named steganography is used to avoid detection of hidden data, which is the aim of transfer of confidential data secretly, and different image formats (like BMP, JPEG, PNG et al.) are discussed.
Abstract: To avoid detection of hidden data, a technique named steganography is used. Transfer of confidential data secretly is the aim of steganography. Discussion of different image formats (like BMP, JPEG, PNG Etc.) for the steganography is presented in this paper. Technical properties, application and limitation of steganography will also be discussed here.
TL;DR: In this article , a watermarking method based on local statistics in pixels is proposed, which is an alternative and simplifier of the quadtree method, dividing the image into identical nonoverlapping blocks and then choosing the block with less energy as more suitable for water marking.
Abstract: In this article, due to the importance of embedding encrypted information in the image, a watermarking method is proposed based on local statistics in pixels. The advantages of the proposed method include its complete reversibility and very high security, which is due to the use of the quadtree concept, finding similar parts in the image, and embedding information in low‐energy and less significant pixels. This method is an alternative and simplifier of the quadtree method, dividing the image into identical non‐overlapping blocks and then choosing the block with less energy as more suitable for watermarking. Also, two criteria of mean‐squared‐error and peak signal‐to‐noise ratio (PSNR) have been calculated and the PSNR shows that image quality has not changed too much after hiding the information than the original image. It should be noted that since the proposed method is applied to black and white images, the result can be generalized to different color channels in the image, and color images have more visible capabilities in terms of cached memory than black and white images because they contain three dimensions of information.
References
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25 Apr 2001
TL;DR: The newly developed algorithm F5 withstands visual and statistical attacks, yet it still offers a large steganographic capacity because it implements matrix encoding to improve the efficiency of embedding and reduces the number of necessary changes.
Abstract: Many steganographic systems are weak against visual and statistical attacks. Systems without these weaknesses offer only a relatively small capacity for steganographic messages. The newly developed algorithm F5 withstands visual and statistical attacks, yet it still offers a large steganographic capacity. F5 implements matrix encoding to improve the efficiency of embedding. Thus it reduces the number of necessary changes. F5 employs permutative straddling to uniformly spread out the changes over the whole steganogram.
1,136 citations
TL;DR: This paper proposes an alternative and well-known machine learning tool-ensemble classifiers implemented as random forests-and argues that they are ideally suited for steganalysis.
Abstract: Today, the most accurate steganalysis methods for digital media are built as supervised classifiers on feature vectors extracted from the media. The tool of choice for the machine learning seems to be the support vector machine (SVM). In this paper, we propose an alternative and well-known machine learning tool-ensemble classifiers implemented as random forests-and argue that they are ideally suited for steganalysis. Ensemble classifiers scale much more favorably w.r.t. the number of training examples and the feature dimensionality with performance comparable to the much more complex SVMs. The significantly lower training complexity opens up the possibility for the steganalyst to work with rich (high-dimensional) cover models and train on larger training sets-two key elements that appear necessary to reliably detect modern steganographic algorithms. Ensemble classification is portrayed here as a powerful developer tool that allows fast construction of steganography detectors with markedly improved detection accuracy across a wide range of embedding methods. The power of the proposed framework is demonstrated on three steganographic methods that hide messages in JPEG images.
967 citations
TL;DR: This paper proposes a universal distortion design called universal wavelet relative distortion (UNIWARD) that can be applied for embedding in an arbitrary domain and demonstrates experimentally using rich models as well as targeted attacks that steganographic methods built using UNIWARD match or outperform the current state of the art in the spatial domain, JPEG domain, and side-informed JPEG domain.
Abstract: Currently, the most successful approach to steganography in empirical objects, such as digital media, is to embed the payload while minimizing a suitably defined distortion function. The design of the distortion is essentially the only task left to the steganographer since efficient practical codes exist that embed near the payload-distortion bound. The practitioner’s goal is to design the distortion to obtain a scheme with a high empirical statistical detectability. In this paper, we propose a universal distortion design called universal wavelet relative distortion (UNIWARD) that can be applied for embedding in an arbitrary domain. The embedding distortion is computed as a sum of relative changes of coefficients in a directional filter bank decomposition of the cover image. The directionality forces the embedding changes to such parts of the cover object that are difficult to model in multiple directions, such as textures or noisy regions, while avoiding smooth regions or clean edges. We demonstrate experimentally using rich models as well as targeted attacks that steganographic methods built using UNIWARD match or outperform the current state of the art in the spatial domain, JPEG domain, and side-informed JPEG domain.
859 citations
TL;DR: This paper proposes a complete practical methodology for minimizing additive distortion in steganography with general (nonbinary) embedding operation and reports extensive experimental results for a large set of relative payloads and for different distortion profiles, including the wet paper channel.
Abstract: This paper proposes a complete practical methodology for minimizing additive distortion in steganography with general (nonbinary) embedding operation. Let every possible value of every stego element be assigned a scalar expressing the distortion of an embedding change done by replacing the cover element by this value. The total distortion is assumed to be a sum of per-element distortions. Both the payload-limited sender (minimizing the total distortion while embedding a fixed payload) and the distortion-limited sender (maximizing the payload while introducing a fixed total distortion) are considered. Without any loss of performance, the nonbinary case is decomposed into several binary cases by replacing individual bits in cover elements. The binary case is approached using a novel syndrome-coding scheme based on dual convolutional codes equipped with the Viterbi algorithm. This fast and very versatile solution achieves state-of-the-art results in steganographic applications while having linear time and space complexity w.r.t. the number of cover elements. We report extensive experimental results for a large set of relative payloads and for different distortion profiles, including the wet paper channel. Practical merit of this approach is validated by constructing and testing adaptive embedding schemes for digital images in raster and transform domains. Most current coding schemes used in steganography (matrix embedding, wet paper codes, etc.) and many new ones can be implemented using this framework.
726 citations
Proceedings Article•
01 Apr 2011
TL;DR: A survey on steganography and steganalysis for digital images, mainly covering the fundamental concepts, the progress of steganographic methods for images in spatial representation and in JPEG format, and the development of the corresponding steganalytic schemes.
Abstract: Steganography and steganalysis are important topics in information hiding. Steganography refers to the technology of hiding data into digital media without drawing any suspicion, while steganalysis is the art of detecting the presence of steganography. This paper provides a survey on steganography and steganalysis for digital images, mainly covering the fundamental concepts, the progress of steganographic methods for images in spatial representation and in JPEG format, and the development of the corresponding steganalytic schemes. Some commonly used strategies for improving steganographic se- curity and enhancing steganalytic capability are summarized and possible research trends are discussed.
417 citations