Publications

2019

• Optimizing System Architecture Cost and Security Countermeasures
  
  • Berro Sahar
  • Apvrille Ludovic
  • Duc Guillaume
  , 2019. The design of an embedded system is built on a trade-off between its performance and its cost. Nowadays, the security threats that target most of the embedded systems introduce a new factor in this trade-off: the security level of the system. So system architects must consider , during the design, the different attacks that target the system and the possible countermeasures, and their costs. In this article, we present a methodology to help designers explore different countermeasures and evaluate their impact on the cost of the architecture and the probability of success of an adversary. This methodology is based on extended and formalized Attack-Defense Trees that allow to assess the impact of countermeasures on system components and attacks. We use propagation rules to characterize a main attack from its different steps, and we formalize the trade-off between security and cost by an optimization problem between attack probability and total architecture cost.
• Temporal characterization of an urban horizontal atmospheric telecom channel
  
  • Sauvage Chloé
  • Robert Clélia
  • Sorrente Béatrice
  • Erasme Didier
  , 2019, pp.PW4C.5. Free Space Optics (FSO) are breakable under some climatic conditions. However characterization of the propagation channel by studying wavelength transmisttance and data coming from a wavefront experiment could improve FSO's performance. (10.1364/PCAOP.2019.PW4C.5)
  DOI : 10.1364/PCAOP.2019.PW4C.5
• Core modal spatial-structuring in inhibited-coupling hollow-core fibers
  
  • Osorio Jonas
  • Chafer Matthieu
  • Debord Benoît
  • Giovanardi Fabio
  • Cordier Martin
  • Maurel Martin
  • Delahaye Frédéric
  • Amrani Foued
  • Vincetti Luca
  • Gérôme Frédéric
  • Benabid Fetah
  , 2019, pp.Paper CE-7.2.
• Physically-Derived 3-Box Power Amplifier Model
  
  • Soleiman Elias
  • Pham Dang-Kièn Germain
  • Jabbour Chadi
  • Desgreys Patricia
  • Kamarei Mahmoud
  , 2019, pp.1-4. (10.1109/NEWCAS44328.2019.8961231)
  DOI : 10.1109/NEWCAS44328.2019.8961231
• Risk Analysis on C-ITS pseudonymity aspects
  
  • Haidar Farah
  • Kaiser Arnaud
  • Lonc Brigitte
  • Urien Pascal
  , 2019. In the near future, vehicles will communicate with their environment by broadcasting Vehicle to everything (V2x) messages over the vehicular network (IEEE 802.11p). The exchanged messages contain data related to driver's privacy. As the laws in Europe require the privacy protection, the solution is to use pseudonym identities (certificates) in the communication. However, the use of these certificates can create new vulnera-bilities that must be taken into account. In this paper, we do a state of art on the existing vulnerabilities, we applied the TVRA method and propose new vulnerabilities. Finally, we propose new countermeasures that could be implemented.
• STAnalyzer: A simple static analysis tool for detecting cache-timing leakages
  
  • Schaub Alexander
  • Rioul Olivier
  • Guilley Sylvain
  , 2019. Cache-timing attacks are a class of side-channel attacks that target software implementations of cryptographic algorithms. If the cache-access pattern of the implementation depends on sensitive information, then a cache-timing attack can retrieve this information, which can potentially lead to a secret-key recovery. Implementations which branch on condi- tions depending on sensitive information, or that access memory locations whose address depend on sensitive information, are potentially vulnerable to such attacks. This paper presents an algorithm for verifying that a program, imple- mented in the C language, is free from cache-timing leakages. It consists in computing the dependencies of all the variables used in the program, and listing all sensible values that leak due to branching and memory accesses. An implementation of this algorithm, STAnalyzer, is also pro- vided. It allows to flag sensitive values, and those are tracked across computations, function calls, etc. Therefore, only leakages of sensitive values are reported. Because the algorithm runs directly on an abstract syntaxic tree (AST) of the C program, the output is straightforward to interpret: dependencies between C variables are reported, as well as the stack of function calls and instructions that lead to the leakage of sensitive values.
• Acceleration of Lightweight Block Ciphers on Microprocessors
  
  • Tehrani Etienne
  • Graba Tarik
  • Danger Jean-Luc
  , 2019. Cryptography is a key element to the development of secure communication in embedded environment such as within or between connected cars. In such constrained devices standard cryptographic algorithms have been considered too costly which lead to the emergence of specific Lightweight Block Ciphers (LBC). The lack of standards alongside industry's desire to use uniquely tweaked LBC calls for a generic and efficient implementation of those algorithms. Microprocessors are a part of most of these embedded systems which allows them to implement any of these algorithms but not efficiently way as it lacks specific instructions. For instance, the RiscV is an open source ISA which can be used in these microprocessors and is currently being enhanced by research through extensions. In this work we propose the study of this ISA and the development of an extension for efficient implementation of LBC. From the state of the art [5], [7] we have selected some LBC based on the following criteria: at least a 128-bit key for security and a 64-bit block size to limit the necessary resources. In order to identify useful extensions, we first identified which parts of LBC are slow when implemented in pure software, and how common they are in state of the art LBC. We only studied the datapath of the cipher as we considered the key scheduling to be part of preprocessing. We used a software implementation of each of the studied algorithms to isolate the costly parts of the ciphers. The computation time was evaluated in number of RiscV assembly language instructions. Studied LBC algorithms exhibit 3 main computation steps: • The key addition which is a simple XOR and doesn't require additional instructions • 8 or 16 4x4 Sbox (common for LBC) which can be implemented as LUT and can be accelerated thanks to the addition of a specific (SIMD) LUT instruction • The diffusion is generally not trivial to implement in pure software and as it can be quite different from one algorithm to the other it is not obvious to provide a unique extension to implement it.
• Reinforcing Protection Against Chosen-Plaintext Attack Using Ciphertext Fragmentation in Multi-cloud Environments
  
  • Kapusta Katarzyna
  • Qiu Han
  • Memmi Gérard
  , 2019, pp.7-9. (10.1109/CSCloud/EdgeCom.2019.00011)
  DOI : 10.1109/CSCloud/EdgeCom.2019.00011
• Barra ferri rotonda in Castel-Minier in the XVth century: from the semi- product to final object, a morphological and metallographic study
  
  • Gosselin Manon
  • Méaudre Jean-Charles
  • Tendero Yohann
  • Dillmann Philippe
  • Téreygeol Florian
  , 2019.
• Re-think Monitoring Service for 5G Network: Challenges and Perspectives
  
  • Tseng Yuchia
  • Aravinthan Gopalasingham
  • Berde Bela
  • Imadali Sofiane
  • Houatra Drissa
  • Qiu Han
  , 2019.
• On the tensor rank of multiplication in finite extensions of finite fields and related issues in algebraic geometry
  
  • Ballet Stéphane
  • Chaumine Jean
  • Pieltant Julia
  • Rambaud Matthieu
  • Randriambololona Hugues
  • Robert Rolland
  , 2019.
• Quantum-Computational Hybrid Cryptography based on the Boolean Hidden Matching Problem
  
  • Alleaume Romain
  , 2019.
• A Diachronic and Statistic Approach of Qualities of Ferrous Alloys: Toward an Automatic Algorithm?
  
  • Gosselin Manon
  • Tendero Yohann
  • Bauvais Sylvain
  • Arribet-Deroin Danielle
  • Pagès Gaspard
  • Téreygeol Florian
  • Dillmann Philippe
  , 2019.
• Sensor Localization System for AR-assisted Disaster Relief Applications (poster)
  
  • Choi Hong-Beom
  • Lim Keun-Woo
  • Ko Young-Bae
  , 2019, pp.526-527. In this poster, we propose a sensor localization system assisted by wireless communication and augmented reality (AR) suitable for disaster relief applications. Generally, disaster environments are considered extremely hazardous and deteriorated, with unpredictable effects to human mobility and digital devices. To maximize the safety and efficiency of first responders, deployment of wireless sensors are of utmost importance, as sensor nodes can provide sensing information as well as location information. We analyze the issues and challenges that need to be tackled for high accuracy localization of sensor nodes in such environments, and then propose a system that we plan to develop in the near future. (10.1145/3307334.3328607)
  DOI : 10.1145/3307334.3328607
• CHARIOT - Towards a Continuous High-Level Adaptive Runtime Integration Testbed
  
  • Barnes Chloe
  • Bellman Kirstie
  • Botev Jean F
  • Diaconescu Ada
  • Esterle Lukas
  • Gruhl Christian
  • Landauer Christopher
  • Lewis Peter
  • Nelson Phyllis
  • Stein Anthony
  • Stewart Christopher
  • Tomforde Sven
  , 2019, pp.52-55. (10.1109/FAS-W.2019.00026)
  DOI : 10.1109/FAS-W.2019.00026
• Integration of Pervasive Platforms with iCasa
  
  • Lalanda Philippe
  • Diaconescu Ada
  , 2019, pp.49-51. (10.1109/FAS-W.2019.00025)
  DOI : 10.1109/FAS-W.2019.00025
• Guided Anisotropic Diffusion and Iterative Learning for Weakly Supervised Change Detection
  
  • Daudt Rodrigo Caye
  • Le Saux Bertrand
  • Boulch Alexandre
  • Gousseau Yann
  , 2019. Large scale datasets created from user labels or openly available data have become crucial to provide training data for large scale learning algorithms. While these datasets are easier to acquire, the data are frequently noisy and unreliable , which is motivating research on weakly supervised learning techniques. In this paper we propose an iterative learning method that extracts the useful information from a large scale change detection dataset generated from open vector data to train a fully convolutional network which surpasses the performance obtained by naive supervised learning. We also propose the guided anisotropic diffusion algorithm , which improves semantic segmentation results using the input images as guides to perform edge preserving filtering , and is used in conjunction with the iterative training method to improve results.
• Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope
  
  • Birdal Tolga
  • Şimşekli Umut
  , 2019. We present an entirely new geometric and probabilistic approach to synchronization of correspondences across multiple sets of objects or images. In particular, we present two algorithms: (1) Birkhoff-Riemannian L-BFGS for optimizing the relaxed version of the combinatorially intractable cycle consistency loss in a principled manner, (2) Birkhoff-Riemannian Langevin Monte Carlo for generating samples on the Birkhoff Polytope and estimating the confidence of the found solutions. To this end, we first introduce the very recently developed Riemannian geometry of the Birkhoff Polytope. Next, we introduce a new probabilistic synchronization model in the form of a Markov Random Field (MRF). Finally, based on the first order retraction operators, we formulate our problem as simulating a stochastic differential equation and devise new integrators. We show on both synthetic and real datasets that we achieve high quality multi-graph matching results with faster convergence and reliable confidence/uncertainty estimates.
• Multi-Scale Feedbacks for Large-Scale Coordination in Self-Systems
  
  • Diaconescu Ada
  • Di Felice Louisa Jane
  • Mellodge Patricia
  , 2019, pp.137-142. Multi-scale structures, or hierarchies, are prevalent in large-scale dynamic systems, from inert matter to living and artificial systems, and systems-of-systems. Yet, a general theory helping to understand and develop multi-scale systems is still missing. This paper identifies common design aspects and variants, and synthesises them via a novel design pattern - Multi-Scale Feedbacks - to help adaptive coordination in large-scale systems. It also suggests relations between design choices and qualitative properties. The proposed pattern was distilled from a cross-domain study, including particle physics, molecular biology, neuroscience, insect and human organisations, ecosystems, autonomous control and systems-of-systems. (10.1109/SASO.2019.00025)
  DOI : 10.1109/SASO.2019.00025
• Field trial test and monitoring of W-band point to multipoint wireless network
  
  • Ramirez Antonio
  • Martinez Miguel
  • Leder Etienne
  • Willebois Joel
  • Magne François
  • André Frédéric
  • Le Quang Trung
  • Begaud Xavier
  • Krozer Viktor
  • Marilier Marc
  • Letizia Rosa
  • Llorente Roberto
  • Zimmermann Ralph
  • Paoloni Claudio
  , 2019.
• Diversité spatiale, temporelle et fréquentielle pour la mesure précise de distance et d'angle d'arrivée en ultra large bande
  
  • Vo Tien Tu
  , 2019. De nos jours, la détection et la mesure de la distance avec les ondes électromagnétiques (Radar) sont utilisées dans de nombreux domaines tels que l’aéronautique, l’automobile ou bien la médecine. Dans cette thèse, nous nous intéressons plus particulièrement au Radar dans le domaine du bien-être pour le grand public : capteur sans contact pour le suivi du sommeil, et lunettes ou canne pour malvoyants pour la détection des obstacles sur la route. Le problème posé dans cette thèse est d’ajouter les fonctionnalités nécessaires suivantes à la solution Radar existante afin de répondre à ces applications : la mesure du rythme respiratoire issu du déplacement de la cage thoracique et de l'abdomen de quelques millimètres pendant la respiration et la mesure de la direction d'arrivée de l'onde électromagnétique rétro-diffusée des obstacles devant le malvoyant. Le contexte technologique de départ est celui de la technologie ultra large bande qui offre une résolution de l’ordre du centimètre pour la mesure de distance à une portée de quelques mètres et la discrimination des signaux rétro-diffusés des multiples obstacles. Suivant les besoins, les travaux décrits ici se sont concentrés sur le canal de propagation en rétro-diffusion sur corps humain. Ils se sont aussi portés sur les techniques de traitement du signal pour pouvoir estimer le rythme respiratoire dans le signal rétro-diffusé du corps humain, et sur l'estimation de la direction d'arrivée de l'onde à un réseau d'antennes avec une résolution au degré près. Enfin, cette thèse aborde l’architecture du système, et notamment du récepteur associé au réseau d'antennes, afin de pouvoir réaliser la mesure angulaire sans augmenter la complexité, le coût et la consommation du récepteur.
• Two-Metric Helper Data for Highly Robust and Secure Delay PUFs
  
  • Danger Jean-Luc
  • Guilley Sylvain
  • Schaub Alexander
  , 2019, pp.184-188. (10.1109/IWASI.2019.8791249)
  DOI : 10.1109/IWASI.2019.8791249
• Processus alpha-stables pour le traitement du signal
  
  • Fontaine Mathieu
  , 2019. Le sujet scientifique de la séparation de sources sonores (SSS) vise à décomposer les signaux audio en leurs éléments constituants, par exemple en séparant la voix du chanteur principal de son accompagnement musical ou du bruit de fond. Dans le cas d’enregistrements historiques très anciens et très dégradés, la SSS étend de manière significative les méthodes classiques de débruitage en permettant de prendre en compte des motifs complexes de signal et de bruit et de réaliser efficacement la séparation, là où les approches traditionnelles sont tenues en échec. En traitement du signal audio, le signal observé est souvent supposé être égal à la somme des signaux que nous souhaitons obtenir. Dans le cadre d’une modélisation probabiliste, il est alors primordial que les processus stochastiques préservent leur loi par sommation. Le processus le plus employé et vérifiant cette stabilité est le processus gaussien. Comparé aux autres processus α−stables vérifiant la même stabilité, les processus gaussiens ont la particularité d’admettre des outils statistiques facilement interprétables comme la moyenne et la covariance. L’existence de ces moments permet d’esquisser des méthodes statistiques en SSS et plus généralement, en traitement du signal. La faiblesse de ces processus réside néanmoins dans l’incapacité à s’écarter trop loin de leurs moyennes. Cela limite la dynamique des signaux modélisables et peut provoquer des instabilités dans les méthodes d’inférence considérées. Les processus α−stables non-gaussiens soulèvent des défis mathématiques et ont déjà démontré leur efficacité dans des applications de filtrage et en terme algorithmique. En dépit de non-existence d’une forme analytique des densités de probabilités, les processus α−stables jouissent de résultats non valables dans le cas gaussien. Par exemple, un vecteur α−stable non-gaussien admet une représentation spatiale unique. En résumé, le comportement d’une distribution multivariée α−stable est contrôlé par deux opérateurs. Une mesure dite «spectrale» informant sur l’énergie globale venant de chaque direction de l’espace et un vecteur localisant le centroïde de sa densité de probabilité. Cette représentation spatiale a notamment montré son efficacité dans le cas de la SSS pour la célèbre analyse en composantes indépendantes (ACI). Les modèles pour cette ACI α−stable ne sont cependant proposés que dans le cas de mélanges linéaires instantanés. Par conséquent, l’information dans le domaine fréquentiel est omise pour ce type de mélange. Ce mémoire de thèse introduit différents modèles α−stables d’un point de vue théorique et les développe dans plusieurs directions. Nous proposons notamment une extension de la théorie de filtrage α−stable monocanal au cas multicanal. En particulier, une nouvelle représentation spatiale pour les vecteurs α−stables est adoptée. Nous développons en outre un modèle de débruitage où le bruit et la parole découlent de distributions α−stables mais ayant un exposant caractéristique α différent. La valeur d’α permet de contrôler la stationnarité de chaque source. Grâce à ce modèle hybride, nous avons également déduit une explication rigoureuse sur des filtrages de Wiener heuristiques esquissés dans les années 80. Une autre partie de ce manuscrit décrit en outre comment la théorie α−stable permet de fournir une méthode pour la localisation de sources sonores. Pour ce faire, nous employons la représentation spatiale d’un vecteur α−stable non-gaussien afin d’exploiter sa mesure spectrale. En pratique, elle nous permet d’en déduire si une source est active à un endroit précis de l’espace. Au final, nos travaux ont consisté à étudier la théorie α−stable pour le traitement du signal. Nous avons abouti à de nombreux modèles pour un large panel d’applications. En dehors des quelques applications que nous avons déjà considérées, nous pouvons étendre les modèles multicanaux α−stables à la déréverbération ou à la SSS. Quant au modèle sur la localisation des sources sonores, il pourrait être employé afin de déterminer la géométrie d’une salle.
• Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization
  
  • Gower Robert M
  • Hanzely Filip
  • Richtárik Peter
  • Stich Sebastian U
  , 2019. We present the first accelerated randomized algorithm for solving linear systems in Euclidean spaces. One essential problem of this type is the matrix inversion problem. In particular, our algorithm can be specialized to invert positive definite matrices in such a way that all iterates (approximate solutions) generated by the algorithm are positive definite matrices themselves. This opens the way for many applications in the field of optimization and machine learning. As an application of our general theory, we develop the first accelerated (deterministic and stochastic) quasi-Newton updates. Our updates lead to provably more aggressive approximations of the inverse Hessian, and lead to speed-ups over classical non-accelerated rules in numerical experiments. Experiments with empirical risk minimization show that our rules can accelerate training of machine learning models.
• A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
  
  • Şimşekli Umut
  • Sagun Levent
  • Gurbuzbalaban Mert
  , 2019. The gradient noise (GN) in the stochastic gradient descent (SGD) algorithm is often considered to be Gaussian in the large data regime by assuming that the classical central limit theorem (CLT) kicks in. This assumption is often made for mathematical convenience, since it enables SGD to be analyzed as a stochastic differential equation (SDE) driven by a Brownian motion. We argue that the Gaussianity assumption might fail to hold in deep learning settings and hence render the Brownian motion-based analyses inappropriate. Inspired by non-Gaussian natural phenomena, we consider the GN in a more general context and invoke the generalized CLT (GCLT), which suggests that the GN converges to a heavy-tailed $\alpha$-stable random variable. Accordingly, we propose to analyze SGD as an SDE driven by a L\'{e}vy motion. Such SDEs can incur `jumps', which force the SDE transition from narrow minima to wider minima, as proven by existing metastability theory. To validate the $\alpha$-stable assumption, we conduct extensive experiments on common deep learning architectures and show that in all settings, the GN is highly non-Gaussian and admits heavy-tails. We further investigate the tail behavior in varying network architectures and sizes, loss functions, and datasets. Our results open up a different perspective and shed more light on the belief that SGD prefers wide minima.