Secure Cover Selection Steganography (original) (raw)
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Cover Selection for More Secure Steganography
International Journal of Security and Its Applications, 2018
The lack of a cover bank with minimum detectability against various steganalysis methods is one of the major concerns in the field of secure communication. This paper introduces a method for preparing cover images with appropriate security. To this end, some important features of the image such as contrast, energy, and the use of fuzzy logic are considered by selecting the Harris threshold level. First, using each cover image, some images are obtained with different contrasts and a constant Harris threshold level; besides, in order to extract the above-mentioned features, the "Gray Level Co-occurrence Matrices" (GLCM) are calculated. Then, using the fuzzy logic, different security levels are presented for images. The images with different security levels could be stored in different image banks. Afterwards, to achieve lower detectability a stegangraphy against a steganalyzer technique, the difference were obtained between features of clean and stego images, and then to evaluate the performance of each feature, "Area Under the Curve" (AUC) values were calculated using the steganalyzer to the "Fisher Linear Discriminant" (FLD) classification. Actually, the cover bank is formed through cover classification based on an index pre-steganography security level.
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...
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.
Investigation of Steganalysis Algorithms for multiple Cover Media
Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. Steganalysis is the art and science of detecting messages hidden using steganography; this is analogous to cryptanalysis applied to cryptography. In this paper, we provide a critical review of the steganalysis algorithms available to analyze the characteristics of an image, audio or video stego media vis-à-vis the corresponding cover media (without the hidden information) and understand the process of embedding the information and its detection. It is noteworthy that each of these cover media has different special attributes that are altered by a steganography algorithm in such a way that the changes are not perceivable for the unintended recipients; but, the changes are identifiable using appropriate steganlysis algorithms. 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 steganlysis algorithms.
Journal of Global Research in Computer Science, 2011
The staggering growth in communication technology and usage of public domain channels (i.e. Internet) has greatly facilitated transfer of data. However, such open communication channels have greater vulnerability to security threats causing unauthorized information access. Traditionally, encryption is used to realize the communication security. However, important information is not protected once decoded. Steganography is the art and science of communicating in a way which hides the existence of the communication. Important information is firstly hidden in a host data, such as digital image, text, video or audio, etc, and then transmitted secretly to the receiver. Steganalysis is another important topic in information hiding which is the art of detecting the presence of steganography. This paper provides a critical review of steganography as well as to analyze the characteristics of various cover media namely image, text, a u d i o and video in respects of the fundamental concepts, the progress of steganographic methods and the development of the corresponding steganalysis schemes.
A Survey on Digital Image Steganography and Steganalysis
IOSR Journal of Electronics and Communication Engineering, 2013
Steganography is an information security approach used to hide messages inside suitable covers in such a way that it is not known to attackers. The cover files may be any digital data including Image or Audio files. For steganography several methods exists where each of them has some advantages and disadvantages. Steganographic applications have varying requirements depending upon the steganography technique used. In this paper we present an overview of image steganography and steganalsysis, its uses and techniques. It also attempts to identify the requirements of a good steganographic algorithm and compares their performance with respect to requirements.
Quantitative steganalysis of digital images: estimating the secret message length
Multimedia Systems, 2003
The objective of steganalysis is to detect messages hidden in cover objects, such as digital images. In practice, the steganalyst is frequently interested in more than whether or not a secret message is present. The ultimate goal is to extract and decipher the secret message. However, in the absence of the knowledge of the stego technique and the stego and cipher keys, this task may be extremely time consuming or completely infeasible. Therefore, any additional information, such as the message length or its approximate placement in image features, could prove very valuable to the analyst. In this paper, we present general principles for developing steganalytic methods that can accurately estimate the number of changes to the cover image imposed during embedding. Using those principles, we show how to estimate the secret message length for the most common embedding archetypes, including the F5 and OutGuess algorithms for JPEG, EzStego algorithm with random straddling for palette images, and the classical LSB embedding with random straddling for uncompressed image formats. The paper concludes with an outline of ideas for future research such as estimating the steganographic capacity of embedding algorithms.
In this paper, we introduce a new feature-based steganalytic method for JPEG images and use it as a benchmark for comparing JPEG steganographic algorithms and evaluating their embedding mechanisms. The detection method is a linear classifier trained on feature vectors corresponding to cover and stego images. In contrast to previous blind approaches, the features are calculated as an L 1 norm of the difference between a specific macroscopic functional calculated from the stego image and the same functional obtained from a decompressed, cropped, and recompressed stego image. The functionals are built from marginal and joint statistics of DCT coefficients. Because the features are calculated directly from DCT coefficients, conclusions can be drawn about the impact of embedding modifications on detectability. Three different steganographic paradigms are tested and compared. Experimental results reveal new facts about current steganographic methods for JPEGs and new design principles for more secure JPEG steganography. system is considered broken. For a more exact treatment of the concept of steganographic security, the reader is referred to [1,2].
Improvements of Steganography Parameter in Binary Images and JPEG Images against Steganalysis.
International Journal of Engineering Sciences & Research Technology, 2013
Steganography is a science of hiding messages into multimedia documents. A message can be hidden in a document only if the content of a document has high redundancy. Although the embedded message changes the characteristics and nature of the document, it is required that these changes are difficult to be identified by an unsuspecting user. On the other hand, steganalysis develops theories, methods and techniques that can be used to detect hidden messages in multimedia documents. The documents without any hidden messages are called cover documents and the documents with hidden messages are named stego documents. The work of this research paper concentrates on image steganalysis. We present four different types of steganalysis techniques. These steganalysis techniques are developed to counteract the steganographic methods that use binary (black and white) images as the cover media. Unlike grayscale and color images, binary images have a rather modest statistical nature. This makes it difficult to apply directly the existing steganalysis on binary images.