Puisque les ordinateurs sont omniprésents dans notre société et que, de plus en plus, nous dépendons de programmes pour accomplir nos activités de tous les jours, les bogues peuvent parfois avoir des conséquences cruciales. Une grande proportion des programmes existants sont écrits en C ou en C++ et la plupart des erreurs avec ces langages sont dues à l’absence de sûreté d’accès à la mémoire. Notre objectif à long terme est d’être en mesure de vérifier si un programme C ou C++ accède correctement à la mémoire malgré les défauts de ces langages. À cette fin, nous avons créé un cadre de développement d’analyses statiques que nous présentons dans ce mémoire. Il permet de construire des analyses à partir de petits composants réutilisables qui sont liés automatiquement par métaprogrammation. Il incorpore également le modèle de conception (design pattern) du visiteur et des algorithmes utiles pour faire de l’analyse statique. De plus, il fournit un modèle objet pour le RTL, la représentation intermédiaire de bas niveau pour tous les langages supportés par GCC. Ceci implique qu’il est possible de concevoir des analyses indépendantes des langages de programmation. Nous décrivons également les modules que comporte l’analyse statique que nous avons développée à l’aide de notre cadre d’analyse et qui vise à vérifier si un programme respecte les règles d’accès à la mémoire. Cette analyse n’est pas complète, mais elle est conçue pour être améliorée facilement. Autant le cadre d’analyse que les modules d’analyse des accès à la mémoire sont distribués dans RTL-Check, un logiciel libre. / Since computers are ubiquitous in our society and we depend more and more on programs to accomplish our everyday activities, bugs can sometimes have serious consequences. A large proportion of existing programs are written in C or C++ and the main source of errors with these programming languages is the absence of memory safety. Our long term goal is to be able to verify if a C or C++ program accesses memory correctly in spite of the deficiencies of these languages. To that end, we have created a static analysis framework which we present in this thesis. It allows building analyses from small reusable components that are automatically bound together by metaprogramming. It also incorporates the visitor design pattern and algorithms that are useful for the development of static analyses. Moreover, it provides an object model for RTL, the low-level intermediate representation for all languages supported by GCC. This implies that it is possible to design analyses that are independent of programming languages. We also describe the modules that comprise the static analysis we have developed using our framework and which aims to verify if a program is memory-safe. This analysis is not yet complete, but it is designed to be easily improved. Both our framework and our memory access analysis modules are distributed in RTL-Check, an open-source project.

Les plateformes mobiles font partie intégrante du quotidien. Leur flexibilité a permis aux développeurs d’applications d’y proposer des applications de toutes sortes : productivité, jeux, messageries, etc. Devenues des outils connectés d’agrégation d’informations personnelles et professionnelles, ces plateformes sont perçues comme un écosystème lucratif par les concepteurs de maliciels. Android est un système d’exploitation libre de Google visant le marché des appareils mobiles et est l’une des cibles de ces attaques, en partie grâce à la popularité de celuici. Dans la mesure où les maliciels Android constituent une menace pour les consommateurs, il est essentiel que la recherche visant l’analyse de maliciels s’intéresse spécifiquement à cette plateforme mobile. Le travail réalisé dans le cadre de cette maîtrise s’est intéressé à cette problématique, et plus spécifiquement par l’analyse de la mémoire vive. À cette fin, il a fallu s’intéresser aux tendances actuelles en matière de maliciels sur Android et les approches d’analyses statiques et dynamiques présentes dans la littérature. Il a été, par la suite, proposé d’explorer l’analyse de la mémoire vive appliquée à l’analyse de maliciels comme un complément aux approches actuelles. Afin de démontrer l’intérêt de l’approche pour la plateforme Android, une étude de cas a été réalisée où un maliciel expérimental a été conçu pour exprimer les comportements malicieux problématiques pour la plupart des approches relevées dans la littérature. Une approche appelée l’analyse différentielle de la mémoire vive a été présentée afin de faciliter l’analyse. Cette approche utilise le résultat de la différence entre les éléments présents après et avant le déploiement du maliciel pour réduire la quantité d’éléments à analyser. Les résultats de cette étude ont permis de démontrer que l’approche est prometteuse en tant que complément aux approches actuelles. Il est recommandé qu’elle soit le sujet d’études subséquentes afin de mieux détecter les maliciels sur Android et d’en automatiser son application. / Mobile devices are at the core of modern society. Their versatility has allowed third-party developers to generate a rich experience for the user through mobile apps of all types (e.g. productivity, games, communications). As mobile platforms have become connected devices that gather nearly all of our personal and professional information, they are seen as a lucrative market by malware developers. Android is an open-sourced operating system from Google targeting specifically the mobile market and has been targeted by malicious activity due the widespread adoption of the latter by the consumers. As Android malwares threaten many consumers, it is essential that research in malware analysis address specifically this mobile platform. The work conducted during this Master’s focuses on the analysis of malwares on the Android platform. This was achieved through a literature review of the current malware trends and the approaches in static and dynamic analysis that exists to mitigate them. It was also proposed to explore live memory forensics applied to the analysis of malwares as a complement to existing methods. To demonstrate the applicability of the approach and its relevance to the Android malwares, a case study was proposed where an experimental malware has been designed to express malicious behaviours difficult to detect through current methods. The approach explored is called differential live memory analysis. It consists of analyzing the difference in the content of the live memory before and after the deployment of the malware. The results of the study have shown that this approach is promising and should be explored in future studies as a complement to current approaches.

For the last twenty years, several assumptions have been expressed in the fields of information processing, neurophysiology and cognitive sciences. First, neural networks and their dynamical behaviors in terms of attractors is the natural way adopted by the brain to encode information. Any information item to be stored in the neural network should be coded in some way or another in one of the dynamical attractors of the brain, and retrieved by stimulating the network to trap its dynamics in the desired item’s basin of attraction. The second view shared by neural network researchers is to base the learning of the synaptic matrix on a local Hebbian mechanism. The third assumption is the presence of chaos and the benefit gained by its presence. Chaos, although very simply produced, inherently possesses an infinite amount of cyclic regimes that can be exploited for coding information. Moreover, the network randomly wanders around these unstable regimes in a spontaneous way, thus rapidly proposing alternative responses to external stimuli, and being easily able to switch from one of these potential attractors to another in response to any incoming stimulus. Finally, since their introduction sixty years ago, cell assemblies have proved to be a powerful paradigm for brain information processing. After their introduction in artificial intelligence, cell assemblies became commonly used in computational neuroscience as a neural substrate for content addressable memories. <p> <p>Based on these assumptions, this thesis provides a computer model of neural network simulation of a brain-like memory. It first shows experimentally that the more information is to be stored in robust cyclic attractors, the more chaos appears as a regime in the background, erratically itinerating among brief appearances of these attractors. Chaos does not appear to be the cause, but the consequence of the learning. However, it appears as an helpful consequence that widens the network’s encoding capacity. To learn the information to be stored, two supervised iterative Hebbian learning algorithm are proposed. One leaves the semantics of the attractors to be associated with the feeding data unprescribed, while the other defines it a priori. Both algorithms show good results, even though the first one is more robust and has a greater storing capacity. Using these promising results, a biologically plausible alternative to these algorithms is proposed using cell assemblies as substrate for information. Even though this is not new, the mechanisms underlying their formation are poorly understood and, so far, there are no biologically plausible algorithms that can explain how external stimuli can be online stored in cell assemblies. This thesis provide such a solution combining a fast Hebbian/anti-Hebbian learning of the network's recurrent connections for the creation of new cell assemblies, and a slower feedback signal which stabilizes the cell assemblies by learning the feed forward input connections. This last mechanism is inspired by the retroaxonal hypothesis. <p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

In this thesis we provide a model for a bufferless optical burst switching (OBS) and an optical packet switching (OPS) network. The thesis is divided in three parts. <p><p>In the first part we introduce the basic functionality and structure of OBS and OPS networks. We identify the blocking probability as the main performance parameter of interest. <p><p>In the second part we study the statistical properties of the traffic that will likely run through these networks. We use for this purpose a set of traffic traces obtained from the Universidad Politécnica de Catalunya. Our conclusion is that traffic entering the optical domain in future OBS/OPS networks will be long-range dependent (LRD). <p><p>In the third part we present the model for bufferless OBS/OPS networks. This model takes into account the results from the second part of the thesis concerning the LRD nature of traffic. It also takes into account specific issues concerning the functionality of a typical bufferless packet-switching network. The resulting model presents scalability problems, so we propose an approximative method to compute the blocking probability from it. We empirically evaluate the accuracy of this method, as well as its scalability. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished