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Balado, Félix
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Balado, Félix
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Balado, Félix
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Now showing 1 - 10 of 18
- PublicationOptimum Reversible Data Hiding and Permutation CodingThis 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.
417 - PublicationA Modified Watermark Synchronisation Code for Robust Embedding of Data in DNADNA 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 simulations
843 - PublicationPerformance of DNA data embedding algorithms under substitution mutations(2010-12)
; DNA data embedding is a relatively recent area which aims at embedding arbitrary information in deoxyribonucleic acid (DNA) strands. One interesting application of DNA data embedding can be tracing pathways of genetic material in novel ways. This paper explores the decoding performance of several DNA data embedding algorithms proposed in the literature, which are also briefly reviewed. DNA may undergo random mutations, which can cause errors at the decoding stage of such algorithms. Although some proposed methods do account for such errors, decoding performance under mutations has not been previously studied in general. The empirical performance comparison that we provide here allows to fairly compare a number of DNA data embedding algorithms under mutations for the first time. The evaluation is undertaken by means of Monte Carlo simulations. Additionally, we propose two new DNA data embedding algorithms with good robustness properties.726 - PublicationGene Tagging and the Data Hiding RateWe analyze the maximum number of ways in which one can intrinsically tag a very particular kind of digital asset: a gene, which is just a DNA sequence that encodes a protein. We consider gene tagging under the most relevant biological constraints: protein encoding preservation with and without codon count preservation. We show that our finite and deterministic combinatorial results are asymptotically—as the length of the gene increases— particular cases of the stochastic Gel’fand and Pinsker capacity formula for communications with side information at the encoder, which lies at the foundations of data hiding theory. This is because gene tagging is a particular case of DNA watermarking.
425 - PublicationThe role of permutation coding in minimum-distortion perfect counterforensicsThis 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.
439 - PublicationSecurity of keyed DNA data embeddingThe emergent field of DNA data embedding has, in the past decade, seen the proposal of many methods to encode data in the genome of living organisms. These algorithms have primarily focused on incorporating error correction into encoded data. However the security aspects of data encoded in DNA have generally been overlooked. As with any data hiding method, information encoded in DNA can be protected with a secret key known only to authorized individuals. While there have been suggestions to incorporate keys, no well defined functions for mapping keys to parameters have been proposed yet. Furthermore there have been no security analyses of keyed DNA data embedding methods, in terms of quantifying how difficult it is for an attacker to find the key. In this paper, modifications to incorporate secret keys into a prominent embedding algorithm are proposed, and the security is analysed under realistic attack scenarios. The algorithm to be modified, called BioCode ncDNA has been proposed by us, and is designed for encoding data in vivo (in the cells of living organism) with high biocompatibility and near-optimum embedding rate.
222 - PublicationOn the Shannon capacity of DNA data embeddingThis 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.
612Scopus© Citations 8 - PublicationOptimum Exact Histogram SpecificationExact 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.
539Scopus© Citations 5 - PublicationRepetition coding as an effective error correction code for embedding information in DNAThe 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.
389Scopus© Citations 11 - PublicationAsymptotically Optimum Perfect Universal Steganography of Finite Memoryless SourcesA solution to the problem of asymptotically optimum perfect universal steganography of finite memoryless sources with a passive warden is provided, which is then extended to contemplate a distortion constraint. The solution rests on the fact that Slepian’s Variant I permutation coding implements firstorder perfect universal steganography of finite host signals with optimum embedding rate. The duality between perfect universal steganography with asymptotically optimum embedding rate and lossless universal source coding with asymptotically optimum compression rate is evinced in practice by showing that permutation coding can be implemented by means of adaptive arithmetic coding. Next, a distortion constraint between the host signal and the information-carrying signal is considered. Such a constraint is essential whenever real-world host signals with memory (e.g., images, audio, or video) are decorrelated to conform to the memoryless assumption. The constrained version of the problem requires trading off embedding rate and distortion. Partitioned permutation coding is shown to be a practical way to implement this trade-off, performing close to an unattainable upper bound on the rate-distortion function of the problem.
604Scopus© Citations 3