Secure steganography based on embedding capacity (original) (raw)
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Steganography capacity: A steganalysis perspective
SPIE Security and Watermarking of …, 2003
Two fundamental questions in steganography are addressed in this paper, namely, (a) definition of steganography security and (b) definition of steganographic capacity. Since the main goal of steganography is covert communications, we argue that these definitions must be dependent on the type of steganalysis detector employed to break the embedding algorithm. We propose new definitions for security and capacity in the presence of a steganalyst. The intuition and mathematical notions supporting these definitions are described. Some numerical examples are also presented to illustrate the need for this investigation.
A Review Of Image Security With Steganography Using Dct Coefficient And Encryption
2016
In the mid 1998s the rise of the internet & multimedia techniques has prompted increasing interest in hiding data in digital media. Early research concentrated on watermarking to protect copyrighted multimedia products. In today's growing world Image data security is the essential portion in communication and multimedia world .The least significant-bit (LSB) based technique is one of the popular for steganography. Medium integrity is an important issue in steganography, whenever one media is hidden into other the originality of cover media should not affect. Image Security with Steganography using DCT Coefficient and Encryption providing security of data & helps to avoid third party access of data is the challenging world. https://journalnx.com/journal-article/20150087
Steganalysis of DCT-embedding based adaptive steganography and YASS
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security - MM&Sec '11, 2011
Recently well-designed adaptive steganographic systems, including ±1 embedding in the DCT domain with optimized costs to achieve the minimal-distortion , have posed serious challenges to steganalyzers. Additionally, although the steganalysis of Yet Another Steganographic Scheme (YASS) was actively conducted, the detection of the YASS steganograms by a large B-block parameter has not been well explored.
Multimedia Tools and Applications, 2019
Digital steganography is becoming a common tool for protecting sensitive communications in various applications such as crime/terrorism prevention whereby law enforcing personals need to remotely compare facial images captured at the scene of crime with faces databases of known criminals/suspects; exchanging military maps or surveillance video in hostile environment/situations; privacy preserving in the healthcare systems when storing or exchanging patient's medical images/records; and prevent bank customers' accounts/records from being accessed illegally by unauthorized users. Existing digital steganography schemes for embedding secret images in cover image files tend not to exploit various redundancies in the secret image bit-stream to deal with the various conflicting requirements on embedding capacity, stego-image quality, and undetectibility. This paper is concerned with the development of innovative image procedures and data hiding schemes that exploit, as well as increase, similarities between secret image bitstream and the cover image LSB plane. This will be achieved in two novel steps involving manipulating both the secret and the cover images, prior to embedding, to achieve higher 0:1 ratio in both the secret image bit-stream and the cover image LSB plane. We exploit the above two steps strategy to use a bit-plane(s) mapping technique, instead of bit-plane(s) replacement to make each cover pixel usable for secret embedding. We shall demonstrate that this strategy produces stego-images that have minimal distortion, high embedding efficiency, reasonably good stego-image quality and robustness against 3 well-known targeted steganalysis tools.
An Optimal Steganalysis Based Approach for Embedding Information in Image Cover Media with Security
World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 2016
This paper deals with the study of interest in the fields of Steganography and Steganalysis. Steganography involves hiding information in a cover media to obtain the stego media in such a way that the cover media is perceived not to have any embedded message for its unintended recipients. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can lead to the prevention of disastrous security incidents. In this paper, we provide a critical review of the steganalysis algorithms available to analyze the characteristics of an image stego media against the corresponding cover media and understand the process of embedding the information and its detection. We anticipate that this paper can also give a clear picture of the current trends in steganography so that we can develop and improvise appropriate steganalysis algorithms. Keywords—Optimization, heuristics and metaheuristics algorithms, embedded systems, low-power consumption, Steganalys...
Journal of theoretical and applied information technology, 2014
Steganography is the art of hiding data and an effort to conceal the existence of the embedded information. There are a lot of data to be embedded such as text, image, audio, and video. An information hiding system is characterized by having three different aspects that contend with each other. These are capacity, security, and robustness. In steganography area, the common method used to hide a secret data is LSB (Least Significant Bit). LSB provides the high embedding capacity, however, when the secret data is larger than cover data, the cover data would be dramatically distorted. The distorted cover data can attract the attacker to perform steganalysis method. This study is carried out to overcome the embedding capacity problem without producing a significant distortion in cover data. The experiment is tested by hiding audio signals in image file. The idea is to convert the audio signals into native data representation (unsigned integer 8) and to find its unique values. The image ...
6 JPEG Steganography System with Minimal Changes to the Quantized DCT Coefficients
Steganography is the science of invisible communications over an innocuous cover medium. Most steganographic systems defeat both visual and first order statistical attacks however they offer only low capacity embedding. In this paper, a new steganographic system is introduced for message embedding by inverting the LSB of DCT coefficients of JPEG image. This algorithm offers high capacity compared to existing steganographic system. Index terms-JPEG hiding, steganography, steganalysis, information hiding. Alaa M. Hamdy received his M.Sc. degree in computer engineering from Helwan University in1996 and his PhD degree from the faculty of electrical engineering, Poznan University of technology, Poland in 2004. Currently he is an assistant professor at faculty of engineering, Helwan University. His research interests in the field of image processing, pattern analysis and machine vision.
Adaptive batch steganography considering image embedding capacity
Optical Engineering, 2009
The problem of spreading secret data to embed into multiple cover images is called batch steganography and has been theoretically considered recently. Few works have been done in batch steganography, and in all of them, the payload is spread between cover images unwisely. We present the Adaptive batch steganography ͑ABS͒ approach and consider embedding capacity as a property of images. ABS is an approach to adaptively spread secret data among multiple cover images based on their embedding capacity. By splitting the payload based on image embedding capacity constraint, embedding can be done more secure than the state when the embedder does not know how much data can be hidden securely in an image. Furthermore, the number of required cover images to embed a piece of secret data in ABS is smaller than the number of required cover images in usual batch steganography. We apply an ensemble system that uses different steganalyzer units to determine the embedding capacity of a cover image. Each steganalyzer unit is formed by a combination of multiple steganalyzers from a same type, but each one trained to detect a certain payload. Experimental results showed the effectiveness of embedding in ABS and security enhancement of produced stego images.
CSIS: Compressed sensing‐based enhanced‐embedding capacity image steganography scheme
IET Image Processing, 2021
Image steganography plays a vital role in securing secret data by embedding it in the cover images. Usually, these images are communicated in a compressed format. Existing techniques achieve this but have low embedding capacity. Enhancing this capacity causes a deterioration in the visual quality of the stego-image. Hence, our goal here is to enhance the embedding capacity while preserving the visual quality of the stego-image. We also intend to ensure that our scheme is resistant to steganalysis attacks. This paper proposes a Compressed Sensing Image Steganography (CSIS) scheme to achieve our goal while embedding binary data in images. The novelty of our scheme is the combination of three components in attaining the above-listed goals. First, we use compressed sensing to sparsify cover image block-wise, obtain its linear measurements, and then uniquely select permissible measurements. Further, before embedding the secret data, we encrypt it using the Data Encryption Standard (DES) algorithm, and finally, we embed two bits of encrypted data into each permissible measurement. This is the first attempt to rigorously embed more than one bit. Second, we propose a novel data extraction technique, which is lossless and completely recovers our secret data. Third, for the reconstruction of the stego-image, we use the least absolute shrinkage and selection operator (LASSO) for the resultant optimization problem. This has the advantages of fast convergence and easy implementation. This component is also new. We perform experiments on several standard grayscale images and a color image, and evaluate embedding capacity, Peak Signal-to-Noise Ratio (PSNR) value, mean Structural Similarity (SSIM) index, Normalized Cross-Correlation (NCC) coefficients, and entropy. We achieve 1.53 times more embedding capacity as compared to the most recent scheme. We obtain an average of 37.92 dB PSNR value, and average values close to 1 for both the mean SSIM index and the NCC coefficients, which are considered good. Moreover, the entropy of cover images and their corresponding stego-images are nearly the same. These assessment metrics show that CSIS substantially outperforms existing similar steganography schemes. pp. 1-xii i