arXiv subjects

Jacques M. Bahi

Publications and source records attributed to Jacques M. Bahi.

At least 19 recordsLinked to original sources

arXiv2017

An improved watermarking scheme for Internet applications

In this paper, a data hiding scheme ready for Internet applications is proposed. An existing scheme based on chaotic iterations is improved, to respond to some major Internet security concerns, such as digital rights management, communication over hidden channels, and social search engines. By using Reed Solomon error correcting codes and wavelets domain, we show that this data hiding scheme can be improved to solve issues and requirements raised by these Internet fields.

cs.MM↗

arXiv2017

A Cryptographic Approach for Steganography

In this research work, security concepts are formalized in steganography, and the common paradigms based on information theory are replaced by another ones inspired from cryptography, more practicable are closer than what is usually done in other cryptographic domains. These preliminaries lead to a first proof of a cryptographically secure information hiding scheme.

cs.CR↗

arXiv2017

A Robust Data Hiding Process Contributing to the Development of a Semantic Web

In this paper, a novel steganographic scheme based on chaotic iterations is proposed. This research work takes place into the information hiding framework, and focus more specifically on robust steganography. Steganographic algorithms can participate in the development of a semantic web: medias being on the Internet can be enriched by information related to their contents, authors, etc., leading to better results for the search engines that can deal with such tags. As media can be modified by users for various reasons, it is preferable that these embedding tags can resist to changes resulting from some classical transformations as for example cropping, rotation, image conversion, and so on. This is why a new robust watermarking scheme for semantic search engines is proposed in this document. For the sake of completeness, the robustness of this scheme is finally compared to existing established algorithms.

cs.MM↗

arXiv2017

An optimization technique on pseudorandom generators based on chaotic iterations

Internet communication systems involving cryptography and data hiding often require billions of random numbers. In addition to the speed of the algorithm, the quality of the pseudo-random number generator and the ease of its implementation are common practical aspects. In this work we will discuss how to improve the quality of random numbers independently from their generation algorithm. We propose an additional implementation technique in order to take advantage of some chaotic properties. The statistical quality of our solution stems from some well-defined discrete chaotic iterations that satisfy the reputed Devaney's definition of chaos, namely the chaotic iterations technique. Pursuing recent researches published in the previous International Conference on Evolving Internet (Internet 09, 10, and 11), three methods to build pseudorandom generators by using chaotic iterations are recalled. Using standard criteria named NIST and DieHARD (some famous batteries of tests), we will show that the proposed technique can improve the statistical properties of a large variety of defective pseudorandom generators, and that the issues raised by statistical tests decrease when the power of chaotic iterations increase.

cs.CR↗

arXiv2017

A Pipeline for Insertion Sequence Detection and Study for Bacterial Genome

Insertion Sequences (ISs) are small DNA segments that have the ability of moving themselves into genomes. These types of mobile genetic elements (MGEs) seem to play an essential role in genomes rearrangements and evolution of prokaryotic genomes, but the tools that deal with discovering ISs in an efficient and accurate way are still too few and not totally precise. Two main factors have big effects on IS discovery, namely: genes annotation and functionality prediction. Indeed, some specific genes called "transposases" are enzymes that are responsible of the production and catalysis for such transposition, but there is currently no fully accurate method that could decide whether a given predicted gene is either a real transposase or not. This is why authors of this article aim at designing a novel pipeline for ISs detection and classification, which embeds the most recently available tools developed in this field of research, namely OASIS (Optimized Annotation System for Insertion Sequence) and ISFinder database (an up-to-date and accurate repository of known insertion sequences). As this latter depend on predicted coding sequences, the proposed pipeline will encompass too various kinds of bacterial genes annotation tools (that is, Prokka, BASys, and Prodigal). A complete IS detection and classification pipeline is then proposed and tested on a set of 23 complete genomes of Pseudomonas aeruginosa. This pipeline can also be used as an investigator of annotation tools performance, which has led us to conclude that Prodigal is the best software for IS prediction. A deepen study regarding IS elements in P.aeruginosa has then been conducted, leading to the conclusion that close genomes inside this species have also a close numbers of IS families and groups.

q-bio.GN↗

arXiv2017

Traversing a n-cube without Balanced Hamiltonian Cycle to Generate Pseudorandom Numbers

This article presents a new class of Pseudorandom Number Generators. The generators are based on traversing a n-cube where a Balanced Hamiltonian Cycle has been removed. The construction of such generators is automatic for small number of bits, but remains an open problem when this number becomes large. A running example is used throughout the paper. Finally, first statistical experiments of these generators are presented, they show how efficient and promising the proposed approach seems.

cs.DS↗

arXiv2017

Relation between Insertion Sequences and Genome Rearrangements in Pseudomonas aeruginosa

During evolution of microorganisms genomes underwork have different changes in their lengths, gene orders, and gene contents. Investigating these structural rearrangements helps to understand how genomes have been modified over time. Some elements that play an important role in genome rearrangements are called insertion sequences (ISs), they are the simplest types of transposable elements (TEs) that widely spread within prokaryotic genomes. ISs can be defined as DNA segments that have the ability to move (cut and paste) themselves to another location within the same chromosome or not. Due to their ability to move around, they are often presented as responsible of some of these genomic recombination. Authors of this research work have regarded this claim, by checking if a relation between insertion sequences (ISs) and genome rearrangements can be found. To achieve this goal, a new pipeline that combines various tools have firstly been designed, for detecting the distribution of ORFs that belongs to each IS category. Secondly, links between these predicted ISs and observed rearrangements of two close genomes have been investigated, by seeing them with the naked eye, and by using computational approaches. The proposal has been tested on 18 complete bacterial genomes of Pseudomonas aeruginosa, leading to the conclusion that IS3 family of insertion sequences are related to genomic inversions.

q-bio.GN↗

arXiv2017

Dependability of Sensor Networks for Industrial Prognostics and Health Management

Maintenance is an important activity in industry. It is performed either to revive a machine/component or to prevent it from breaking down. Different strategies have evolved through time, bringing maintenance to its current state: condition-based and predictive maintenances. This evolution was due to the increasing demand of reliability in industry. The key process of condition-based and predictive maintenances is prognostics and health management, and it is a tool to predict the remaining useful life of engineering assets. Nowadays, plants are required to avoid shutdowns while offering safety and reliability. Nevertheless, planning a maintenance activity requires accurate information about the system/component health state. Such information is usually gathered by means of independent sensor nodes. In this study, we consider the case where the nodes are interconnected and form a wireless sensor network. As far as we know, no research work has considered such a case of study for prognostics. Regarding the importance of data accuracy, a good prognostics requires reliable sources of information. This is why, in this paper, we will first discuss the dependability of wireless sensor networks, and then present a state of the art in prognostic and health management activities.

cs.SE↗

arXiv2017

A Security Framework for Wireless Sensor Networks: Theory and Practice

Wireless sensor networks are often deployed in public or otherwise untrusted and even hostile environments, which prompts a number of security issues. Although security is a necessity in other types of networks, it is much more so in sensor networks due to the resource-constraint, susceptibility to physical capture, and wireless nature. In this work we emphasize two security issues: (1) secure communication infrastructure and (2) secure nodes scheduling algorithm. Due to resource constraints, specific strategies are often necessary to preserve the network's lifetime and its quality of service. For instance, to reduce communication costs nodes can go to sleep mode periodically (nodes scheduling). These strategies must be proven as secure, but protocols used to guarantee this security must be compatible with the resource preservation requirement. To achieve this goal, secure communications in such networks will be defined, together with the notions of secure scheduling. Finally, some of these security properties will be evaluated in concrete case studies.

cs.DC↗

arXiv2017

Taenia Biomolecular Phylogeny and the Impact of Mitochondrial Genes on this Latter

Variations in mitochondrial genes are usually considered to infer phylogenies. However some of these genes are lesser constraint than other ones, and thus may blur the phylogenetic signals shared by the majority of the mitochondrial DNA sequences. To investigate such effects, in this research work, the molecular phylogeny of the genus Taenia is studied using 14 coding sequences extracted from mitochondrial genomes of 17 species. We constructed 16,384 trees, using a combination of 1 up to 14 genes. We obtained 131 topologies, and we showed that only four particular instances were relevant. Using further statistical investigations, we then extracted a particular topology, which displays more robustness properties.

q-bio.PE↗

arXiv2017

Hash functions using chaotic iterations

In this paper, a novel formulation of discrete chaotic iterations in the field of dynamical systems is given. Their topological properties are studied: it is mathematically proved that, under some conditions, these iterations have a chaotic behavior in the meaning of Devaney. This chaotic behavior allows us to propose a way to generate new hash functions. An illustration example is detailed in order to show how to use our theoretical study in practice.

cs.CR↗

arXiv2017

Low Cost Monitoring and Intruders Detection using Wireless Video Sensor Networks

There is a growing interest in the use of video sensor networks in surveillance applications in order to detect intruders with low cost. The essential concern of such networks is whether or not a specified target can pass or intrude the monitored region without being detected. This concern forms a serious challenge to wireless video sensor networks of weak computation and battery power. In this paper, our aim is to prolong the whole network lifetime while fulfilling the surveillance application needs. We present a novel scheduling algorithm where only a subset of video nodes contribute significantly to detect intruders and prevent malicious attacker to predict the behavior of the network prior to intrusion. Our approach is chaos-based, where every node based on its last detection, a hash value and some pseudo-random numbers easily computes a decision function to go to sleep or active mode. We validate the efficiency of our approach through theoretical analysis and demonstrate the benefits of our scheduling algorithm by simulations. Results show that in addition of being able to increase the whole network lifetime and to present comparable results against random attacks (low stealth time), our scheme is also able to withstand malicious attacks due to its fully unpredictable behavior.

cs.CR↗

arXiv2017

Predicting the Evolution of Gene $ura3$ in the Yeast Saccharomyces Cerevisiae

Since the late `60s, various genome evolutionary models have been proposed to predict the evolution of a DNA sequence as the generations pass. Most of these models are based on nucleotides evolution, so they use a mutation matrix of size 4x4. They encompass for instance the well-known models of Jukes and Cantor, Kimura, and Tamura. By essence, all of these models relate the evolution of DNA sequences to the computation of the successive powers of a mutation matrix. To make this computation possible, particular forms for the mutation matrix are assumed, which are not compatible with mutation rates that have been recently obtained experimentally on gene ura3 of the Yeast Saccharomyces cerevisiae. Using this experimental study, authors of this paper have deduced a simple mutation matrice, compute the future evolution of the rate purine/pyrimidine for ura3, investigate the particular behavior of cytosines and thymines compared to purines, and simulate the evolution of each nucleotide.

q-bio.PE↗

arXiv2016

Randomness and disorder of chaotic iterations. Applications in information security field

Design and cryptanalysis of chaotic encryption schemes are major concerns to provide secured information systems. Pursuing our previous research works, some well-defined discrete chaotic iterations that satisfy the reputed Devaney's definition of chaos have been proposed. In this article, we summarize these contributions and propose applications in the fields of pseudorandom number generation, hash functions, and symmetric cryptography. For all these applications, the proofs of chaotic properties are outlined.

nlin.CD↗

arXiv2016

Theoretical Design and FPGA-Based Implementation of Higher-Dimensional Digital Chaotic Systems

Traditionally, chaotic systems are built on the domain of infinite precision in mathematics. However, the quantization is inevitable for any digital devices, which causes dynamical degradation. To cope with this problem, many methods were proposed, such as perturbing chaotic states and cascading multiple chaotic systems. This paper aims at developing a novel methodology to design the higher-dimensional digital chaotic systems (HDDCS) in the domain of finite precision. The proposed system is based on the chaos generation strategy controlled by random sequences. It is proven to satisfy the Devaney's definition of chaos. Also, we calculate the Lyapunov exponents for HDDCS. The application of HDDCS in image encryption is demonstrated via FPGA platform. As each operation of HDDCS is executed in the same fixed precision, no quantization loss occurs. Therefore, it provides a perfect solution to the dynamical degradation of digital chaos.

nlin.CD↗

arXiv2016

Using an epidemiological approach to maximize data survival in the internet of things

The internet of things (IoT) has gained worldwide attention in recent years. It transforms the everyday objects that surround us into proactive actors of the Internet, generating and consuming information. An important issue related to the appearance of such large-scale self-coordinating IoT is the reliability and the collaboration between the objects in the presence of environmental hazards. High failure rates lead to significant loss of data. Therefore, data survivability is a main challenge of the IoT. In this paper, we have developed a compartmental e-Epidemic SIR (Susceptible-Infectious-Recovered) model to save the data in the network and let it survive after attacks. Furthermore, our model takes into account the dynamic topology of the network where natural death (crashing nodes) and birth are defined and analyzed. Theoretical methods and simulations are employed to solve and simulate the system of equations developed and to analyze the model.

cs.DC↗

arXiv2016

Relaxing the Hypotheses of Symmetry and Time-Reversibility in Genome Evolutionary Models

Various genome evolutionary models have been proposed these last decades to predict the evolution of a DNA sequence over time, essentially described using a mutation matrix. By essence, all of these models relate the evolution of DNA sequences to the computation of the successive powers of the mutation matrix. To make this computation possible, hypotheses are assumed for the matrix, such as symmetry and time-reversibility, which are not compatible with mutation rates that have been recently obtained experimentally on genes ura3 and can1 of the Yeast Saccharomyces cerevisiae. In this work, authors investigate systematically the possibility to relax either the symmetry or the time-reversibility hypothesis of the mutation matrix, by investigating all the possible matrices of size 2*2 and 3*3. As an application example, the experimental study on the Yeast Saccharomyces cerevisiae has been used in order to deduce a simple mutation matrix, and to compute the future evolution of the rate purine/pyrimidine for $ura3$ on the one hand, and of the particular behavior of cytosines and thymines compared to purines on the other hand.

q-bio.BM↗

arXiv2016

Neural Networks and Chaos: Construction, Evaluation of Chaotic Networks, and Prediction of Chaos with Multilayer Feedforward Networks

Many research works deal with chaotic neural networks for various fields of application. Unfortunately, up to now these networks are usually claimed to be chaotic without any mathematical proof. The purpose of this paper is to establish, based on a rigorous theoretical framework, an equivalence between chaotic iterations according to Devaney and a particular class of neural networks. On the one hand we show how to build such a network, on the other hand we provide a method to check if a neural network is a chaotic one. Finally, the ability of classical feedforward multilayer perceptrons to learn sets of data obtained from a dynamical system is regarded. Various Boolean functions are iterated on finite states. Iterations of some of them are proven to be chaotic as it is defined by Devaney. In that context, important differences occur in the training process, establishing with various neural networks that chaotic behaviors are far more difficult to learn.

cs.NE↗