The Least Significant Bit (LSB) embedding technique is a well-known and broadly employed method in multimedia
steganography, used mainly in applications involving single bit-plane manipulations in the spatial domain [1]. The key
advantages of LSB procedures are they are simple to understand, easy to implement, have high embedding capacity, and
can be resistant to steganalysis attacks. Additionally, the LSB approach has spawned numerous applications and can be
used as the basis of more complex techniques for multimedia data embedding. In the last several decades, hundreds of
new LSB or LSB variant methods have been developed in an effort to optimize capacity while minimizing detectability,
taking advantage of the overall simplicity of this method. LSB-steganalysis research has also intensified in an effort to
find new or improved ways to evaluate the performance of this widely used steganographic system. This paper reviews
and categorizes some of these major techniques of LSB embedding, focusing specifically on the spatial domain. Some
justification for establishing and identifying promising uses of a proposed SD-LSB centric taxonomy are discussed.
Specifically, we define a new taxonomy for SD-LSB embedding techniques with the goal of aiding researchers in tool
classification methodologies that can lead to advances in the state-of-the-art in steganography. With a common
framework to work with, researchers can begin to more concretely identify core tools and common techniques to
establish common standards of practice for steganography in general. Finally, we provide a summary on some of the
most common LSB embedding techniques followed by a proposed taxonomy standard for steganalysis.
This paper introduces a new redundant number system, the adjunctive numerical relation (ANR) codes, which offer
improvements over other well known systems such as the Fibonacci, Lucas, and the Prime number systems when used in
multimedia data hiding applications. It will be shown that this new redundant number system has potential applications
in digital communications, signal, and image processing. the paper will also offer two illustrative applications for this
new redundant coding system. First an enhanced bit-plane decomposition of image formatted files with data embedding
(steganography and watermarking). Secondly, an example of an expanded bit-line decomposition of audio formatted
files with data embedding and index-based retrieval capability will be described. The computer simulations will detail
the statistical stability required for effective data encoding techniques and demonstrate the improvements in the
embedding capacity in multimedia carriers.
We introduce a technique for covertly embedding data throughout an audio file using redundant number system
decomposition across non-standard digital bit-lines. This bit-line implementation integrates an index recoverable
embedded algorithm with an extended bit level representation that achieves a high capacity data channel within an audio
multimedia file. It will be shown this new steganography method has minimal aural distortive affects while preserving
both first and second order cover statistics, making it less susceptible to most steganalysis attacks. Our research
approach involves reviewing the common numerical methods used in common binary-based algorithms. We then
describe basic concepts and challenges when attempting to implement complex embedding algorithms that are based on
redundant number systems. Finally, we introduce a novel class of numerical based multiple bit-line decomposition
systems, which we define as Adjunctive Numerical Representations. The system is primarily described using basic PCM
techniques in uncompressed audio files however extended applications for alternate multimedia is addressed. This new
embedding system will not only provide the statistical stability required for effective steganography but will also give us
an improvement in the embedding capacity in this class of multimedia carrier files. This novelty of our approach is
demonstrated by an ability to embed high capacity covert data while simultaneously providing a means for rapid,
indexed data recovery.
In this paper, we introduce a novel technique for covertly embedding data throughout an image using redundant number
system decomposition over non-standard digital bit planes. It will be shown that this new steganography method has
minimal visual distortive affects while also preserving both first and second order cover statistics, making it less
susceptible to most general steganalysis attacks. This paper begins by reviewing the common numerical methods used
in today's binary-based steganography algorithms. We then describe some the basic concepts and challenges when
attempting to implement complex embedding algorithms that are based on a redundant number system. Finally, we
introduce a novel class of numerical based multiple bit-plane decomposition systems, which we define as Adjunctive
Numerical Representations. This new system will not only provide the statistical stability required for effective
steganography but will also give us an improvement in the embedding capacity for our multimedia carrier files.
KEYWORDS: Multimedia, Steganography, Digital watermarking, Steganalysis, Statistical analysis, Distortion, Data communications, Binary data, Digital signal processing, Signal processing
Over the past several years there has been an apparent shift in research focus in the area of digital steganography and
steganalysis - a shift from primarily image based methods to a new focus on broader multimedia techniques. More
specifically the area of digital audio steganography is of prime interest. We introduce a new high capacity, covert
channel data embedding and recovery system for digital audio carrier files using a key based encoding and decoding
method. It will be shown that the added information file is interleaved within the carrier file and is fully indexed
allowing for segmented extraction and recovery of data at chosen start and stop points in the sampled stream. The
original audio quality is not affected by the addition of this covert data. The embedded information can also be secured
by a binary key string or cryptographic algorithm and resists statistical analytic detection attempts. We will also
describe how this new method can be used for data compression and expansion applications in the transfer and storage of
digital multimedia to increase the overall data capacity and security.
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