59 research outputs found
The role of permutation coding in minimum-distortion perfect counterforensics
No full text39th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May, 2014This paper exploits the connection between minimum-distortion perfect counterforensics and maximum-rate perfect steganography in order to provide the optimum solution to the first of these problems, in the case in which the forensic detector solely uses first order statistics. The solution relies on Slepian’s variant I permutation codes, which had previously been shown to implement maximum
rate perfect steganography when the host is memoryless (equivalently, when the steganographic detector only uses first-order statistics). Additionally, we demonstrate a blind counterforensic strategy made possible by permutation decoding, which may also find application in image processing.Science Foundation IrelandAD 28/04/201
Optimum Reversible Data Hiding and Permutation Coding
No full text7th IEEE International Workshop on Information Forensics and Security (WIFS), Rome, Italy, 16 - 19 November, 2015This paper is mainly devoted to investigating the connection between binary reversible data hiding and permutation coding. We start by undertaking an approximate combinatorial analysis of the embedding capacity of reversible watermarking in the binary Hamming case, which asymptotically shows that optimum reversible watermarking must involve not only 'writing on dirty paper', as in any blind data hiding scenario, but also writing on the dirtiest parts of the paper. The asymptotic analysis leads to the information-theoretical result given by Kalker and Willems more than a decade ago. Furthermore, the novel viewpoint of the problem suggests a near-optimum reversible watermarking algorithm for the low embedding distortion regime based on permutation coding. A practical implementation of permutation coding, previously proposed in the context of maximum-rate perfect steganography of memoryless hosts, can be used to implement the algorithm. The paper concludes with a discussion on the evaluation of the general rate-distortion bound for reversible data hiding.University College Dubli
Optimum Exact Histogram Specification
No full text2018 IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Alberta, Canada (ICASSP-2018), 15-20 April 2018Exact histogram specification (EHS) is a classic image processing problem which generalises histogram equalisation. Over the years, no optimum solution to the EHS problem has been given with respect to any similarity criterion. An analytic and efficient solution to the optimum EHS problem, according to the mean squared error (MSE) criterion, is presented here. The inverse problem is also examined, and closed-form performance analyses are given in both cases
On the Shannon capacity of DNA data embedding
No full text2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Dallas, USA, March 14-19, 2010This paper firstly gives a brief overview of information embedding in deoxyribonucleic acid (DNA) sequences and its applications. DNA data embedding can be considered as a particular case of communications with or without side information, depending on the use of coding or noncoding DNA sequences, respectively. Although several DNA data embedding methods have been proposed over the last decade, it is still an open question to determine the maximum amount of information that can theoretically be embedded - that is, its Shannon capacity. This is the main question tackled in this paper.Science Foundation Irelandti ke SB. 26/7/1
Permutation Codes and Steganography
No full text38th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May, 2013We show that Slepian’s Variant I permutation codes implement first-order perfect steganography (i.e., histogram-preserving steganography). We give theoretical expressions for the embedding distortion, embedding rate and embedding efficiency of permutation codes in steganography, which demonstrate that these codes conform to prior
analyses of the properties of capacity-achieving perfect stegosystems with a passive warden. We also propose a modification of adaptive arithmetic coding that near optimally implements permutation coding with a low complexity, confirming all our theoretical predictions. Finally we discuss how to control the embedding distortion. Permutation
coding turns out to be akin to Sallee’s model-based steganography, and to supersede both this method and LSB matching.SFI Research FrontiersPossibly to be published by IEEE - if not published, remove IEEE details - OR 10/06/2013TS 14.06.1
Improving Data Hiding Performance by Using Quantization in a Projected Domain
No full textThe quantization of a linear projective transformation first proposed by Chen and Wornell is shown to allow for much better performance figures than those yielded by previous approaches. The procedure to achieve this improvement is explained through the proposal and analysis of an improved data hiding method called Quantized Projection (QP), based in the quantization of a statistic similar to those used at detection in spread-spectrum algorithms. Both the theoretical analysis and the empirical validation show that projectionbased methods exhibit huge performance improvements over existing ones under the same conditions ---i.e. same degree of diversity and level of random additive attacking distortion. 1
Repetition coding as an effective error correction code for embedding information in DNA
No full text11th IEEE International Conference on Bioinformatics and Bioengineering (BIBE), 24-26, October 2011, Taichung, TaiwanThe goal of DNA data embedding is to enable robust encoding of non-genetic information in DNA. This field straddles the areas of bioinformatics and digital communications, since DNA mutations can be seen as akin to a noisy channel from the point of view of information encoding. In this paper we present two algorithms which, building on a variant of a method proposed by Yachie et al., rely on repetition coding to effectively counteract the impact that mutations have on an embedded message. The algorithms are designed for resynchronising multiple, originally identical, information encoded DNA sequences, embedded within non-coding DNA (ncDNA) sections of a host genome. They use both BLAST and MUSCLE algorithms to accomplish this. Bit error rates at the decoder are established for mutations rates accumulated over a number of generations of the host organism. The empirical results obtained are compared to a theoretical bound for optimal decoding.Science Foundation IrelandConference detailshttp://bibe2011.asia.edu.tw/BIBE'11 not yet published
ti - kpw8/12/1
A Modified Watermark Synchronisation Code for Robust Embedding of Data in DNA
No full textPoster presentation at the 38th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), May 23-31, 2013, Vancouver, CanadaDNA data embedding is a newly emerging field aspiring to encode
data in deoxyribonucleic acid (DNA). DNA is an inherently
digital and noisy medium, undergoing substitution, insertion and
deletion mutations. Hence, encoding information in DNA can be
seen as a particular case of digital communications in which biological
constraints must be observed. In this paper we propose a modification
of Davey and MacKay’s watermark synchronisation code
(unrelated to digital watermarking) to create an encoding procedure
more biocompatible with the host organism than previous methods.
In addition, when combined with a low density parity check (LDPC)
code, the method provides near-optimum error correction. We also
obtain the theoretical embedding capacity of DNA under substitution
mutations for the increased biocompatibility constraint. This result,
along with an existing bound on capacity for insertion and deletion
mutations, is compared to the proposed algorithm’s performance by
means of Monte Carlo simulationsScience Foundation IrelandSFI Research FrontiersPossibly to be published by IEEE - if not published remove IEEE copyright statement and details from publisher field - OR 10/06/2013SB. 18.6.201
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