In this paper, we propose a new adaptive embedding technique which decomposes the image into various bitplanes
based on redundant number systems. This technique is driven by three separate functions: 1) Adaptive selection
of locations and number of bits per pixel to embed. 2) Adaptive selection of bit-plane decomposition for the cover
image. 3) Adaptive selection of manner in which the information is inserted. Through the application of sensitive
directional-based statistical estimation and a recorded account of actions taken, the proposed algorithms are able to
provide the desired level of security, both visually and statistically. In comparison with other methods offering the same
level of security, the new technique is able to offer a greater embedding capacity.
This paper introduces a new recursive sequence called the truncated P-Fibonacci sequence, its corresponding binary
code called the truncated Fibonacci p-code and a new bit-plane decomposition method using the truncated Fibonacci pcode.
In addition, a new lossless image encryption algorithm is presented that can encrypt a selected object using this
new decomposition method for privacy protection. The user has the flexibility (1) to define the object to be protected as
an object in an image or in a specific part of the image, a selected region of an image, or an entire image, (2) to utilize
any new or existing method for edge detection or segmentation to extract the selected object from an image or a specific
part/region of the image, (3) to select any new or existing method for the shuffling process. The algorithm can be used in
many different areas such as wireless networking, mobile phone services and applications in homeland security and
medical imaging. Simulation results and analysis verify that the algorithm shows good performance in object/image
encryption and can withstand plaintext attacks.
The technological efficiency and growing research in digital networks, devices, and transmission has made digital
multi-media an increasingly popular alternative to conventional analog media. With the recent advancements in internet
and multi-media technologies, the need for secured multimedia has increased exponentially. In this paper, we present a
logical subband based novel secured multimedia system for digital images that could be used for both data hiding and
cryptographic applications. It decomposes the cover into various integer valued sub-images that also provides the
location map of flippable subband coefficients. Moreover, this approach enhances the capacity of data hiding system by
a significant amount of data and simultaneously reduces the visible distortions that could occur in the image. In addition,
this technique could also be employed for cryptographic applications, as this framework offers lossless recovery of the
scrambled data and effective scrambling. Simulation results show that the proposed technique limits the changes to
boundary regions of the image. Further, this approach can retrieve the embedded information without prior knowledge
of the original unmarked image.
Cellular communications constitute a significant portion of the global telecommunications market. Therefore, the
need for secured communication over a mobile platform has increased exponentially. Steganography is an art of hiding
critical data into an innocuous signal, which provide answers to the above needs. The JPEG is one of commonly used
format for storing and transmitting images on the web. In addition, the pictures captured using mobile cameras are in
mostly in JPEG format.
In this article, we introduce a switching theory based steganographic system for JPEG images which is applicable
for mobile and computer platforms. The proposed algorithm uses the fact that energy distribution among the quantized
AC coefficients varies from block to block and coefficient to coefficient. Existing approaches are effective with a part
of these coefficients but when employed over all the coefficients they show there ineffectiveness. Therefore, we propose
an approach that works each set of AC coefficients with different frame work thus enhancing the performance of the
approach. The proposed system offers a high capacity and embedding efficiency simultaneously withstanding to simple
statistical attacks. In addition, the embedded information could be retrieved without prior knowledge of the cover
image. Based on simulation results, the proposed method demonstrates an improved embedding capacity over existing
algorithms while maintaining a high embedding efficiency and preserving the statistics of the JPEG image after hiding
In recent years, active research has mainly concentrated on authenticating a signature; tracking a document in a digital library, and tamper detection of a scanned document or secured communication using binary images. Binary image steganographical systems provide a solution for the above discussed issues. The two color constraint of the image limits the extension of various LSB embedding techniques to the binary case. In this paper, we present a new data hiding system for binary images and scanned documents. The system initially identifies embeddable blocks and enforces specific block statistics to hide sensitive information. The distribution of the flippable pixels in these blocks is highly uneven over the image. A variable block embedding threshold is employed for capitalizing on this uneven distribution of pixels. In addition, we also present a measure to find the best the cover given a specific file of sensitive information.
The simulation was performed over 50 various binary images such the scanned documents, cartoons, threshold color images. Simulation results shows that 1) The amount of data embedded is comparatively higher than the existing algorithms (such as K.H. Hwang
et.al ,J. Chen et.al ,M.Y.Wu et.al ). 2) The visual distortion in cover image is minimal when compared with the existing algorithms (such as J. Chen,M.Y.Wu et.al ) will be presented.
Adaptive steganography, an intelligent approach to message hiding, integrated with matrix encoding and pn-sequences serves as a promising resolution to recent security assurance concerns. Incorporating the above data hiding concepts with established cryptographic protocols in wireless communication would greatly increase the security and privacy of transmitting sensitive information. We present an algorithm which will address the following problems: 1) low embedding capacity in mobile devices due to fixed image dimensions and memory constraints, 2) compatibility between mobile and land based desktop computers, and 3) detection of stego images by widely available steganalysis software [1-3]. Consistent with the smaller available memory, processor capabilities, and limited resolution associated with mobile devices, we propose a more magnified approach to steganography by focusing adaptive efforts at the pixel level. This deeper method, in comparison to the block processing techniques commonly found in existing adaptive methods, allows an increase in capacity while still offering a desired level of security. Based on computer simulations using high resolution, natural imagery and mobile device captured images, comparisons show that the proposed method securely allows an increased amount of embedding capacity but still avoids detection by varying steganalysis techniques.
Currently, cellular phones constitute a significant portion of the global telecommunications market. Modern cellular phones offer sophisticated features such as Internet access, on-board cameras, and expandable memory which provide these devices with excellent multimedia capabilities. Because of the high volume of cellular traffic, as well as the ability of these devices to transmit nearly all forms of data. The need for an increased level of security in wireless communications is becoming a growing concern. Steganography could provide a solution to this important problem.
In this article, we present a new algorithm for JPEG-compressed images which is applicable to mobile platforms. This algorithm embeds sensitive information into quantized discrete cosine transform coefficients obtained from the cover JPEG. These coefficients are rearranged based on certain statistical properties and the inherent processing and memory constraints of mobile devices. Based on the energy variation and block characteristics of the cover image, the sensitive data is hidden by using a switching embedding technique proposed in this article. The proposed system offers high capacity while simultaneously withstanding visual and statistical attacks.
Based on simulation results, the proposed method demonstrates an improved retention of first-order statistics when compared to existing JPEG-based steganographic algorithms, while maintaining a capacity which is comparable to F5 for certain cover images.
Adaptive steganography is a statistical approach for hiding the digital information into another form of digital media. The goal is to ensure the changes introduced into the cover image remain consistent with the natural noise model associated with digital images. There are generally two classes of steganography − global and local. The global class encompasses all non-adaptive techniques and is the simplest to apply and easiest to detect. The second classification is the local class, which defines most of the present adaptive techniques. We propose a new adaptive technique that is able to overcome embedding capacity limitations and reduce the revealing artifacts that are customarily introduced when applying other embedding methods. To obtain the objectives, we introduce a third faction which is the pixel focused class of steganography. Applying a new adaptive T-order statistical local characterization, the proposed algorithm is able to adaptively select the number of bits to embed per pixel. Additionally, a histogram retention process, an evaluation measure based on the cover image and statistical analysis allow for the embedding of information in a manner which ensures soundness from multiple statistical aspects. Based on the results of simulated experiments, our method is shown to securely allow an increased amount of embedding capacity, simultaneously avoiding detection by varying steganalysis techniques.
Compression is a technique that is used to encode data so that the data needs less storage/memory space. Compression of random data is vital in case where data where we need preserve data that has low redundancy and whose power spectrum is close to noise. In case of noisy signals that are used in various data hiding schemes the data has low redundancy and low energy spectrum. Therefore, upon compressing with lossy compression algorithms the low energy spectrum might get lost. Since the LSB plane data has low redundancy, lossless compression algorithms like Run length, Huffman coding, Arithmetic coding are in effective in providing a good compression ratio. These problems motivated in developing a new class of compression algorithms for compressing noisy signals. In this paper, we introduce a two new compression technique that compresses the random data like noise with reference to know pseudo noise sequence generated using a key. In addition, we developed a representation model for digital media using the pseudo noise signals. For simulation, we have made comparison between our methods and existing compression techniques like Run length that shows the Run length cannot compress when data is random but the proposed algorithms can compress. Furthermore, the proposed algorithms can be extended to all kinds of random data used in various applications.