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We propose a steganographic scheme based on permutations, which improves the capacity of embedding information in a series of p host binary images. Given a host binary image block of size m x n bits and any embedding technique T, where T can hide Q(m, n) bits of data in the image; given p images, T can hide p x Q(m, n) bits of data in these images. Our scheme improves the capacity of embedding information in p images such that, instead of p x Q(m, n) bits, it can hide p x log2(p) + p x Q(m, n)bits. The results which have been obtained by experiments, show that our model performs a better hiding process in terms of hiding capacity.

Hash functions are important cryptographic primitives that map arbitrary length messages to fixed length message summaries such that: it is easy to compute the digest given a message, while invert the hash process (for example, finding a message that maps a summary of a specific message) is difficult. An attack against a hash function is an algorithm that nevertheless manages to invert the hash process. Hash functions are used in authentication, digital signature, and key exchange systems. The most widely used hash function in many applications is the Message Digest-5 (MD5) algorithm. In this paper we study the current state of the technique of realization of the preimage attack of MD5 using solver SAT, we try improvements in the process of encoding and resolution. An important part of our work is to use the methods of propositional logic to model the attack problem and to determine which heuristic leads to the best resolution. Our most important result is a new encoding of the addition to several operands which considerably reduce the time required for the SAT solvers to find a solution to coding’s previously known.

In this paper, we proposed a method that exploits justified texts of PDF files to embed secret data. The method is inspired by the work of Khosravi et al on "A new method for pdf steganography in justified texts" where they proposed a stegosystem allowing to embed in particular lines called a host line, 4 bits of secret message. We've improved it by exposing a combinatorics-based method able not only to embed 7 bits of secret message in these host lines but also b bits (b 0), thus allowing a sender to conceal a bigger message with very few changes made to the cover text.

Community detection in directed networks appears as one of the most relevant topics in the field of network analysis. One of the common themes in its formalizations is information flow clustering i...

Community discovery in networks is one of the most popular topics of modern network science. Given the spread of social networks extracted from applications data, it would be important to recognize that the study of communities in multidimensional networks is becoming a major issue since many individuals can maintain several types of relationships through these applications. The relevance of a dimension in a multidimensional network is an emerging issue that could affect communities’ detection and could be of interest for correlated multidimensional networks meaning those in which there is an equivalence relationship between nodes of different dimensions. The objective of this paper is twofold: (1) providing a study on the importance of relevant dimensions in community detection and (2) presenting an updated overview of some community detection methods in multidimensional networks in order to guide scholars and practitioners in their choices. Afterwards, we highlight some limits and identify features which are forsaken by existing approaches, in order to point up how we can deal with them. Finally, we provide further research directions as well as some open challenges.

Information has always constituted a prized commodity over time, with the strong globalization of exchanges and communications. The provenance, acquisition, protection and integrity of information has always asked major questions, with the strong growth of security needs in many areas around the world. Numerous approaches have been proposed with a view mainly to increase information security. One of them is steganography, where the goal is to conceal the very presence of secret information in a media during a communication. However, this one generally modifies the properties of the cover media used to conceal secret information. Thus, this modification constitutes a vulnerability during the detection and extraction of information concealed in the media, by various steganography attacks. To overcome this problem, Moyou and Ndoundam have proposed a distributed method of data hiding in a multi-cloud storage environment that preserves the property of the cover media, by using different types of media as an index of a part of the secret. However, a security problem is revealed when sharing key between the participating entities in the communication, and the process of managing cloud storage environments between the participating entities can turns to be tedious, depending on the number of cloud accounts used in the method. In order to solve these problems, in this paper we propose a new approach of the method that uses a single cloud storage environment, and strengthens the security of key sharing between the participating entities.

International audience; Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The qua-ternion Fourier transform can be efficiently used to model texture in multidimen-sional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroo-nian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Infection with the hepatitis C virus (HCV) is the most common coinfection in people with the human immunodeficiency virus (HIV), and hepatitis C is categorized as an HIV-related illness. The study of the joint dynamics of HIV and HCV present formidable mathematical challenges in spite the fact that they share similar routes of transmission. A deterministic model for the co-interaction of HCV and HIV in a community is presented and rigorously analyzed. The disease-free equilibrium is shown to be locally asymptotically stable when the associated epidemic threshold known as the basic reproduction number for the model is less than the unity. The Centre Manifold theory is used to show that the HCV only and HIV/AIDS only endemic equilibria are locally asymptotically stable when their associated reproduction numbers are greater than the unity. We compute two coexistence thresholds for the stability of boundary equilibria. Numerical results are presented to validate analytical results.

In this paper, we study the convergence of a mathematical model of opinion dynamics called the majority model. In this model, at each iteration step, each individual adopts the opinion which exerts on him the maximum social pressure. Under some assumptions on interaction among members of the society, we show that, in parallel mode, attractors of the system have period at most two and in sequential mode only fixed points are obtained. We also bound the transient length of iteration graphs of the society in both studied iterating modes.

A cryptographic hash function is a deterministic procedure that compresses an arbitrary block of numerical data and returns a fixed-size bit string. There exists many hash functions: MD5, HAVAL, SHA, ... It was reported that these hash functions are no longer secure. Our work is focused on the construction of a new hash function based on composition of functions. The construction used the NP-completeness of Three-dimensional contingency tables and the relaxation of the constraint that a hash function should also be a compression function., Une fonction de hachage cryptographique est une procédure déterministe qui compresse un ensemble de données numériques de taille arbitraire en une chaîne de bits de taille fixe. Il existe plusieurs fonctions de hachage : MD5, HAVAL, SHA... Il a été reporté que ces fonctions de hachagene sont pas sécurisées. Notre travail a consisté à la construction d’une nouvelle fonction de hachage basée sur une composition de fonctions. Cette construction utilise la NP-completude des tables de contingence de dimension 3 et une relaxation de la contrainte selon laquelle une fonction de hachage doit être aussi une fonction de compression.

We present an online algorithm for routing the automorphisms (BPC permutations) of the queueless MIMD hypercube. The routing algorithm has the virtue of being executed by each node of the hypercube without knowing the state of the others nodes. The algorithm is also vertex and link-contention free. We show, using the proposed algorithm, that BPC permutations are arbitrarily routable in the considered communication model.

We study the cycles generated by the chip firing game associated with n-cube orientations. We consider a particular class of partitions of vertices of n-cubes called left cyclic partitions that induce parallel periodic evolutions. Using this combinatorical model, we show that cycles generated by parallel evolutions are of even lengths from 2 to 2 n on H n (n≥ 1), and of odd lengths different from 3 and ranging from 1 to 2 n − 1-1 on H n (n≥ 4). However, the question weather there exist parallel evolutions with period greater that 2 n remains opened.

Most of the natural shapes have complex volume forms that are usually difficult to model using simple analytical equations. The complexity of the representation is due to the heterogeneity of the physical environment and the variety of phenomena involved. In our study, we are interested by the complex volume shapes structures representation from computed tomographic images. Thanks to the technological advances in Computed Tomography scanners, the image acquisition of complex shapes becomes possible. However, these image data are not directly usable for simulation or modeling purposes. In this thesis, we investigate an approach of modeling of such shapes which consists in making a piecewise approximation of the image data by quadric volumes. We propose to use a split-merge strategy and a region growing algorithm to optimize a function that includes both an approximation error term and a scale factor term that is opposed to it. The input of our algorithms is voxel-based shape description and the result is a set of tangent or disjoint quadric volumes representing the shape in an intrinsic way. We apply our method to represent 3D soil pore space obtained from the Computed Tomography scanners. Within this specific context, we validate our geometrical modeling by performing simulations of water draining and microbial decomposition activities on real data soil sample. This study involves several ecological, agricultural and industrial issues.; Les structures naturelles sont constituées de formes complexes qui sont pour la plupart difficiles à modéliser avec de simples équations analytiques. La complexité de la représentation est due à l'hétérogénéité du milieu physique et à la variété des phénomènes impliqués. Nous nous intéressons dans notre étude à la représentation des structures volumiques complexes issues des images tomographiques. Grâce aux récentes avancées technologiques en tomographie assisté par ordinateur, l’acquisition d'images de formes avec les scanners est maintenant possible. Cependant, ces données images, constituées de voxels, ne sont pas directement utilisables pour simuler un certain nombre de phénomènes. Dans cette thèse, nous proposons une approche de modélisation de ces formes qui consiste à effectuer une approximation par morceaux des données images par des volumes quadriques. Nous proposons d'utiliser une stratégie de division-fusion et un algorithme de croissance de régions pour optimiser une fonctionnelle incluant à la fois un terme erreur d'approximation et un facteur d'échelle. Les données en entrée de notre algorithme sont un ensemble brut de voxels qui décrit une forme volumique complexe et le résultat en sortie est un ensemble de volumes quadriques tangents ou disjoints représentant la forme de départ de façon intrinsèque. Nous appliquons notre méthode pour représenter l'espace poral 3D du sol obtenu à partir des capteurs d'images tomographiques. Ainsi, dans ce contexte spécifique, nous validons notre modélisation géométrique en procédant aux simulations du drainage de l'eau et de l'activité de décomposition microbienne sur des données réelles d'échantillons de sol. Cette étude comporte plusieurs enjeux d’ordres écologique, agricole et industriel.

Most of the natural shapes have complex volume forms that are usually difficult to model using simple analytical equations. The complexity of the representation is due to the heterogeneity of the physical environment and the variety of phenomena involved. In our study, we are interested by the complex volume shapes structures representation from computed tomographic images. Thanks to the technological advances in Computed Tomography scanners, the image acquisition of complex shapes becomes possible. However, these image data are not directly usable for simulation or modeling purposes. In this thesis, we investigate an approach of modeling of such shapes which consists in making a piecewise approximation of the image data by quadric volumes. We propose to use a split-merge strategy and a region growing algorithm to optimize a function that includes both an approximation error term and a scale factor term that is opposed to it. The input of our algorithms is voxel-based shape description and the result is a set of tangent or disjoint quadric volumes representing the shape in an intrinsic way. We apply our method to represent 3D soil pore space obtained from the Computed Tomography scanners. Within this specific context, we validate our geometrical modeling by performing simulations of water draining and microbial decomposition activities on real data soil sample. This study involves several ecological, agricultural and industrial issues.; Les structures naturelles sont constituées de formes complexes qui sont pour la plupart difficiles à modéliser avec de simples équations analytiques. La complexité de la représentation est due à l'hétérogénéité du milieu physique et à la variété des phénomènes impliqués. Nous nous intéressons dans notre étude à la représentation des structures volumiques complexes issues des images tomographiques. Grâce aux récentes avancées technologiques en tomographie assisté par ordinateur, l’acquisition d'images de formes avec les scanners est maintenant possible. Cependant, ces données images, constituées de voxels, ne sont pas directement utilisables pour simuler un certain nombre de phénomènes. Dans cette thèse, nous proposons une approche de modélisation de ces formes qui consiste à effectuer une approximation par morceaux des données images par des volumes quadriques. Nous proposons d'utiliser une stratégie de division-fusion et un algorithme de croissance de régions pour optimiser une fonctionnelle incluant à la fois un terme erreur d'approximation et un facteur d'échelle. Les données en entrée de notre algorithme sont un ensemble brut de voxels qui décrit une forme volumique complexe et le résultat en sortie est un ensemble de volumes quadriques tangents ou disjoints représentant la forme de départ de façon intrinsèque. Nous appliquons notre méthode pour représenter l'espace poral 3D du sol obtenu à partir des capteurs d'images tomographiques. Ainsi, dans ce contexte spécifique, nous validons notre modélisation géométrique en procédant aux simulations du drainage de l'eau et de l'activité de décomposition microbienne sur des données réelles d'échantillons de sol. Cette étude comporte plusieurs enjeux d’ordres écologique, agricole et industriel.