1,777 research outputs found
JPEG steganography with particle swarm optimization accelerated by AVX
Digital steganography aims at hiding secret messages in digital data transmitted over insecure channels. The JPEG format is prevalent in digital communication, and images are often used as cover objects in digital steganography. Optimization methods can improve the properties of images with embedded secret but introduce additional computational complexity to their processing. AVX instructions available in modern CPUs are, in this work, used to accelerate data parallel operations that are part of image steganography with advanced optimizations.Web of Science328art. no. e544
Capacity and Random-Coding Exponents for Channel Coding with Side Information
Capacity formulas and random-coding exponents are derived for a generalized
family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic
upper bounds on the achievable log probability of error. In our model,
information is to be reliably transmitted through a noisy channel with finite
input and output alphabets and random state sequence, and the channel is
selected by a hypothetical adversary. Partial information about the state
sequence is available to the encoder, adversary, and decoder. The design of the
transmitter is subject to a cost constraint. Two families of channels are
considered: 1) compound discrete memoryless channels (CDMC), and 2) channels
with arbitrary memory, subject to an additive cost constraint, or more
generally to a hard constraint on the conditional type of the channel output
given the input. Both problems are closely connected. The random-coding
exponent is achieved using a stacked binning scheme and a maximum penalized
mutual information decoder, which may be thought of as an empirical generalized
Maximum a Posteriori decoder. For channels with arbitrary memory, the
random-coding exponents are larger than their CDMC counterparts. Applications
of this study include watermarking, data hiding, communication in presence of
partially known interferers, and problems such as broadcast channels, all of
which involve the fundamental idea of binning.Comment: to appear in IEEE Transactions on Information Theory, without
Appendices G and
Oblivious data hiding : a practical approach
This dissertation presents an in-depth study of oblivious data hiding with the emphasis on quantization based schemes. Three main issues are specifically addressed:
1. Theoretical and practical aspects of embedder-detector design.
2. Performance evaluation, and analysis of performance vs. complexity tradeoffs.
3. Some application specific implementations.
A communications framework based on channel adaptive encoding and channel independent decoding is proposed and interpreted in terms of oblivious data hiding problem. The duality between the suggested encoding-decoding scheme and practical embedding-detection schemes are examined. With this perspective, a formal treatment of the processing employed in quantization based hiding methods is presented. In accordance with these results, the key aspects of embedder-detector design problem for practical methods are laid out, and various embedding-detection schemes are compared in terms of probability of error, normalized correlation, and hiding rate performance merits assuming AWGN attack scenarios and using mean squared error distortion measure.
The performance-complexity tradeoffs available for large and small embedding signal size (availability of high bandwidth and limitation of low bandwidth) cases are examined and some novel insights are offered. A new codeword generation scheme is proposed to enhance the performance of low-bandwidth applications. Embeddingdetection schemes are devised for watermarking application of data hiding, where robustness against the attacks is the main concern rather than the hiding rate or payload. In particular, cropping-resampling and lossy compression types of noninvertible attacks are considered in this dissertation work
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