PhD Defence: “Privacy Challenges in Wireless Communications of the Internet of Things”, Guillaume Celosia, 22th of September 2020 at 9.30AM

Title

Privacy Challenges in Wireless Communications of the Internet of Things

Abstract

Also known as the Internet of Things (IoT), the proliferation of connected objects offers unprecedented opportunities to consumers. From fitness trackers to medical assistants, through smarthome appliances, the IoT objects are evolving in a plethora of application fields. However, the benefits that they can bring to our society increase along with their privacy implications. Continuously communicating valuable information via wireless links such as Bluetooth and Wi-Fi, those connected devices support their owners within their activities. Most of the time emitted on open channels, and sometimes in the absence of encryption, those information are then easily accessible to any passive attacker in range. In this thesis, we explore two major privacy concerns resulting from the expansion of the IoT and its wireless communications: physical tracking and inference of users information. Based on two large datasets composed of radio signals from Bluetooth/BLE devices, we first defeat existing anti-tracking features prior to detail several privacy invasive applications. Relying on passive and active attacks, we also demonstrate that broadcasted messages contain cleartext information ranging from the devices technical characteristics to personal data of the users such as e-mail addresses and phone numbers. In a second time, we design practical countermeasures to address the identified privacy issues. In this direction, we provide recommendations to manufacturers, and propose an approach to verify the absence of flaws in the implementation of their protocols. Finally, to further illustrate the investigated privacy threats, we implement two demonstrators. As a result, Venom introduces a visual and experimental physical tracking system, while Himiko proposes a human interface allowing to infer information on IoT devices and their owners.

Jury

Kasper Rasmussen – Associate Professor, University of Oxford – Rapporteur
Bernard Tourancheau – Professeur des Universités, Université Grenoble Alpes – Rapporteur
Sonia Ben Mokhtar – Directeur de Recherche, CNRS – Examinateur
Jean-Marie Gorce – Professeur des Universités, INSA Lyon – Examinateur
Vincent Nicomette – Professeur des Universités, INSA Toulouse – Examinateur
Valérie Viet Triem Tong – Professeur des Universités, CentraleSupélec Rennes – Examinateur
Daniel Le Métayer – Directeur de Recherche, Inria – Directeur de thèse
Mathieu Cunche – Maître de Conférences, INSA Lyon – co Directeur de thèse

PhD Defence: “Medium Access Control Layer for Dedicated IoT Networks”, Abderrahman Ben Khalifa, 30th of July 2020 at 2PM

The defense will be available at https://join.skype.com/dbnmuw06rBou

Title

Medium Access Control Layer for Dedicated IoT Networks

Abstract

Les réseaux dédiés pour l’Internet des Objets sont apparus avec la promesse de connecter des milliers de nœuds, voire plus, à une seule station de base dans une topologie en étoile. Cette nouvelle logique représente un changement fondamental dans la façon de penser les réseaux, après des décennies pendant lesquelles les travaux de recherche se sont focalisés sur les réseaux multi-sauts.
Les réseaux pour l’Internet des Objets se caractérisent par la longue portée des transmissions, la vaste couverture géographique, une faible consommation d’énergie et un bas coût de mise en place. Cela a rendu nécessaire des adaptations à tous les niveaux protocolaires afin de satisfaire les besoins de ces réseaux. Plusieurs acteurs sont en concurrence sur le marché de l’Internet des Objets, essayant chacun d’établir la solution la plus efficiente. Ces acteurs se sont concentrés sur la modification de la couche physique, soit au niveau de la partie matérielle, soit par la proposition de nouvelles techniques de modulation. Toutefois, en ce qui concerne la solution de contrôle d’accès au canal (connue sous le nom de couche MAC), toutes les solutions proposées par ces acteurs se fondent sur des approches classiques, tel que Aloha et CSMA.
L’objectif de cette thèse est de proposer une solution MAC dynamique pour les réseaux dédiés à l’Internet des Objets. La solution proposée a la capacité de s’adapter aux conditions du réseau. Cette solution est basée sur un algorithme d’apprentissage automatique, qui apprend de l’historique du réseau afin d’établir la relation entre les conditions du réseau, les paramètres de la couche MAC et les performances du réseau en termes de fiabilité et de consommation d’énergie. La solution possède également l’originalité de faire coexister des nœuds utilisant de différentes configurations MAC au sein du même réseau. Les résultats de simulations ont montré qu’une solution MAC basée sur l’apprentissage automatique pourrait tirer profit des avantages des différents protocoles MAC classiques. Les résultats montrent aussi qu’une solution MAC cognitive offre toujours le meilleur compromis entre fiabilité et consommation d’énergie, tout en prenant en compte l’équité entre les nœuds du réseau. La solution MAC cognitive testée pour des réseaux à haute densité a prouvé des bonnes propriétés de passage à l’échelle par rapport aux protocoles MACs classiques, ce qui constitue un autre atout important de notre solution.

Jury

M. Antoine GALLAIS, Professeur Université Polytechnique Hauts de France, Rapporteur
M. Congduc PHAM, Professeur Université de Pau et des Pays de l’Adour, Rapporteur
Mme. Nancy EL RACHKIDY, Maître de Conférences Université Clermont Auvergne, Examinateur
M. Mickael MAMAN, Ingénieur de Recherche CEA LETI, Examinateur
M. Hervé RIVANO, Professeur INSA Lyon, Directeur de thèse
M. Razvan STANICA, Maître de Conférences INSA Lyon, Co-directeur de thèse

CITI seminar – Mario Zanon (IMT Lucca) – 30/06 at 14:00

Title: Optimal Control, MPC, and Reinforcement Learning

Date and Place: 30 / 06 / 2020 14:00

Speaker: Mario Zanon (Assistant Professor, IMT Lucca, Italy)

Host: Maracas

Abstract: Data-driven control approaches such as Reinforcement Learning (RL) mitigate the issue of model construction and controller tuning by learning directly the (optimal) control law from data. While stunning results have been obtained, RL cannot provide stability nor safety guarantees. Additionally, while partial information on the system is usually available, it can be hard to use it within RL. Model Predictive Control (MPC) is an advanced control technique able to deal with nonlinear systems subject to constraints. The main idea of MPC is to use a mathematical model of the process to predict its future behavior and minimize a given performance index. The advantages of MPC are numerous, as it makes it relatively easy to handle various difficulties in control design, such as dealing with constraints, nonlinear and hybrid dynamics, etc. One of the main drawbacks of MPC is that control performance is highly dependent on the predictive ability of the model. In this seminar, we will discuss how RL and MPC can be combined with the aim of benefitting from the advantages of each while limiting the drawbacks of both. We will introduce the two techniques and present some recent theoretical results, supported by simulation results.

Biography:
Mario Zanon received the Master’s degree in Mechatronics from the University of Trento, and the Diplôme d’Ingénieur from the Ecole Centrale Paris, in 2010. After research stays at the KU Leuven, University of Bayreuth, Chalmers University, and the University of Freiburg he received the Ph.D. degree in Electrical Engineering from the KU Leuven in November 2015. He held a Post-Doc researcher position at Chalmers University until the end of 2017 and is now Assistant Professor at the IMT School for Advanced Studies Lucca. His research interests include numerical methods for optimization, economic MPC, reinforcement learning and optimal control and estimation of nonlinear dynamic systems, in particular for aerospace and automotive applications.

PhD Defence: “Autonomous Wireless Sensor Network Architecture for Vehicular traffic monitoring at an Intersection”, Domga Komguem, 6th of July 2020 at 10AM

The defense will take place at the University of Yaoundé I and will be available at https://join.skype.com/EVc3J1aGhASf

Title

Autonomous Wireless Sensor Network Architecture for Vehicular traffic monitoring at an Intersection

Abstract

In many countries, because of the limited financial budget, the growth of road infrastructures is low compared to the growth of population and the number of vehicles in urban areas. Such a context does not make the task easy for authorities in charge of the management of transportation systems. The introduction of information and communication technologies (ICT) allows to better address these issues. Vehicular traffic management at intersections has an impact on the traffic jam observed in the whole city. In this thesis, our goal is to propose a low-cost, lightweight and autonomous Wireless Sensors Network (WSN) architecture for vehicular traffic monitoring, especially at an intersection. Vehicular traffic data collected can be used, for instance, for intelligent traffic lights management. In the WSN architecture proposed in the literature for vehicular traffic monitoring, underground sensors are used. In terms of network communication, these architectures are not realistic. Nowadays, surface-mounted sensors are proposed by manufacturers.

The first contribution of this thesis is an experimental characterization of wireless links in a WSN with sensors deployed at the ground level. We evaluate the impact of several parameters like the proximity of the ground surface, the communication frequency and the message size on the link quality. Results show a poor link quality at ground level. Based on the conclusions of the experiments, the second contribution of this thesis is WARIM, a new WSN architecture for vehicular traffic monitoring at an intersection. In WARIM, the sensors deployed on a lane form a multi-hop WSN with a linear topology (LWSN). In this network, all the data are forwarded toward the sink. In a network with such properties, the computation and communication requirements are highest in the neighborhood of the sink. Thus, the third contribution of this thesis is a virtual nodes-based and energy efficient sensors deployment strategy for LWSN. Compared to a uniform deployment, this deployment improves the network lifetime by 40%. In our intersection monitoring application, it is important to correlate the messages generated by a sensor to its position with respect to the intersection. Therefore,the fourth contribution of this thesis is, a centroid-based algorithm for sensors ranking in a LWSN. We evaluate the performance of this algorithm considering a realistic channel model, a uniform deployment, as well as the virtual nodes based-deployment proposed in this thesis. Finally, putting all our contributions together, simulations show that WARIM can be used for reliable and real-time vehicular traffic monitoring at an intersection.

Jury

Marcel FOUDA, Professor, Université de Yaoundé I, President
Thomas DJOTIO, Associate Professor, Université de Yaoundé I, Reviewer
Nathalie MITTON, Research Director, INRIA, Reviewer
Bernard TOURANCHEAU, Professor, Université Grenoble Alpes, Reviewer
André-Luc BEYLOT, Professor, ENSEEIHT Toulouse, Examinator
René NDOUNDAM, Associate Professor, Université de Yaoundé I, Examinator
Razvan STANICA, HDR, INSA Lyon, Examinator
Maurice TCHUENTE, Professor, Université de Yaoundé I, Co-Supervisor
Fabrice VALOIS, Professor, INSA Lyon, Co-Supervisor

CITI seminar – Xavier BULTEL (INSA CVL) – 30/01 at 11:00

Title: Sécurité des protocoles de jeux de levées : comment jouer au Bridge avec des tricheurs.

Date and Place: 30 / 01 / 2020 11:00 in TD-C

Speaker: Xavier Bultel (INSA CVL)

Host: Privatics

Abstract:
Les jeux de levées sont des jeux de cartes où chacun des joueurs pose une carte à tour de rôle en fonction d’une règle donnée. Le joueur qui a posé la carte la plus forte gagne la levée, c’est-à-dire toutes les cartes jouées durant la manche. Par exemple, Atout Pique est un jeu de levée très populaire sur les sites de casino en ligne, où chacun des joueurs doit, s’il le peut, jouer une carte de la même couleur que celle de la première carte de la manche. Dans ce genre de jeux, un joueur malhonnête peut jouer une mauvaise carte même s’il à des cartes de la bonne couleur. Comme les autres cartes sont cachées, il est impossible de détecter la triche. Les autres joueurs s’en rendront compte plus tard, lorsque le tricheur jouera une carte qu’il n’est pas sensé avoir. Dans ce cas, le jeu est biaisé et doit être annulé, et l’équipe qui a triché se voit attribuer une pénalité de paiement. cela pose problème si le partenaire du tricheur n’est pas son complice, ce qui est le cas dans les jeux en ligne puisque les joueurs sont appareillés par le serveur du site. Notre but est de proposer un protocole cryptographique qui prévient ce genre de triche. Dans ce tte présentation on définit d’abord un modèle de sécurité pour les protocoles d’Atout Pique sécurisés, puis on construit un protocole appelé SecureSpades. Ce protocole est prouvé sûr dans notre modèle sous l’hypothèse Diffie-Hellman Décisionnel, dans le modèle de l’oracle aléatoire. Notre modèle de sécurité et notre protocole peuvent être étendus à un grand nombre d’autres jeux de levées, comme la Belotte, le Bridge, le Whist, etc.

Biography:
Xavier Bultel, MdC à l’INSA CVL depuis septembre 2019 ; Ex Postdoc à l’IRISA à Rennes (2018-2019) et doctorant au LIMOS à Clermont-Ferrand sous la direction de Pascal Lafourcade (2014-2018).

CITI seminar – Julien Bourgeois (Univ. Bourgogne-Franche-Comté, Institut FEMTO-ST, CNRS) – 23/01 at 14:00

Title: Building programmable matter with micro-robots

Date and Place: 23 / 01 / 2020 14:00 in TD-C

Speaker: Julien Bourgeois (Univ. Bourgogne-Franche-Comté, Institut FEMTO-ST, CNRS)

Host: Olivier Simonin

Abstract:
Technological advances, especially in the miniaturization of robotic devices foreshadow the emergence of large-scale ensembles of small-size resource-constrained robots that distributively cooperate to achieve complex tasks. These ensembles are formed by independent, intelligent and communicating units which act as a whole ensemble which can be used to build programmable matter i.e. matter able to change its shape.
In my talk, I will present our research effort in building Programmable Matter (PM) based on modular robots. To do this, we use micro-technology to scale down the size of each element, and we study geometry, structure, actuation, power, electronics and integration. To manage the complexity of this kind of environment, we propose a complete environment including programmable hardware, a programming language, a compiler, a simulator, a debugger and distributed algorithms.

Biography:
Julien Bourgeois is a professor of computer science at the University of Bourgogne Franche-Comté (UBFC) in France. He is leading the computer science department at the FEMTO-ST institute/CNRS. His research interests include distributed intelligent MEMS (DiMEMS), Programmable Matter, P2P networks and security management for complex networks. He has worked for more than 15 years on these topics and has co-authored more than 160 international publications. He was an invited professor at Carnegie Mellon University (US) from 2012 to 2013, at Emory University (US) in 2011 and at Hong Kong Polytechnic University in 2010, 2011 and 2015. He led different funded research projects (Smart Surface, Smart Blocks, Computation and coordination for DiMEMS). He is currently leading the programmable matter project funded by the ANR and the ISITE-BFC project. He organized and chaired many conferences (dMEMS 2010, 2012, HotP2P/IPDPS 2010, Euromicro PDP 2008 and 2010, IEEE GreenCom 2012, IEEE iThings 2012, IEEE CPSCom 2012, GPC 2012, IEEE HPCC 2014, IEEE ICESS 2014, CSS 2014, IEEE CSE 2016, IEEE EUC 2015, IEEE ATC 2017, IEEE CBDCom 2017).

PhD Defence: “Dynamic Heterogeneous Memory Allocation for embedded devices”, Tristan Delizy, Chappe Amphitheater, CITI, 19th of December 2019 at 10h00

Title

Dynamic Heterogeneous Memory Allocation for embedded devices

Abstract

Reducing energy consumption is a key challenge to the realisation of the Internet of Things. While emerging memory technologies may offer power reduction and high integration density, they come with major drawbacks such as high latency or limited endurance. As a result, system designers tend to juxtapose several memory technologies on the same chip. We aim to provide the embedded application programmer with a transparent software mechanism to leverage this memory heterogeneity. This work studies the interaction between dynamic memory allocation and memory heterogeneity. We provide cycle accurate simulation of embedded platforms with various memory technologies and we show that different dynamic allocation strategies have a major impact on performance. We demonstrates that interesting performance gains can be achieved even for a low fraction of memory using low latency technology, but only with a clever placement strategy between memory banks. We propose an efficient strategy based on application profiling in our simulator.

Jury

Olivier Sentieys, Professeur des Universités, Université de Rennes – Examinateur
Cécile Belleudy, Maitre de Conférence HDR, Université de Nice Sophia Antipolis – Rapporteure
Lionel Torres, Professeur des Universités, Université de Montpellier – Rapporteur
Guillaume Salagnac, Maitre de Conférences, INSA de Lyon – Examinateur, Encadrant
Tanguy Risset, Professeur des Universités, INSA de Lyon – Examinateur, Co-directeur de thèse
Matthieu Moy, Maitre de Conférences HDR, Université Claude Bernard Lyon 1 – Examinateur, Co-directeur de thèse

Journées Nationales de la Recherche en Robotique

Du 14 au 17 octobre, Olivier Simonin a co-présidé avec François Charpillet (Inria Nancy) les JNRR 2019 Journées Nationales de la Recherche en Robotique, qui se sont tenues à Vittel et parrainées par le GDR Robotique. Le 13 octobre était également organisée la Journée des Jeunes Chercheurs en Robotique JJCR, et les 17/18 un tutoriel Apprentissage & Robotique était organisé par Christian Wolf et David Filliat.

L’événement, qui a lieu tous les 2 ans, a eu un fort succès en accueillant 200 participants, qui ont pu suivre 27 exposés scientifiques sur 3 jours.

Site des JNRR 2019 (accès au programme) : https://jnrr2019.loria.fr/

CITI seminar – John Manuel Delgado and Michael Puentes (TInteresaLab de Unidades Tecnológicas de Santander) – 22/11 at 9:00AM

Title: Pedestrian Behavior Modeling and Simulation from Real Time Data Information

Date and Place: 22 / 11 / 2019 09:00 in TD-D

Speaker: John Manuel Delgado and Michael Puentes (TInteresaLab de Unidades Tecnológicas de Santander – UTS, Colombia)

Host: Oscar Carrillo

Abstract:
Accidents of pedestrians sometimes take lives, in Bucaramanga since 2012 pedestrian died by accidents are 179, and 2873 hurt, In a city like Bucaramanga-Colombia, this means each day at least one pedestrian is involved in an accident. Therefore is necessary to know the causes of accidents in the way to decrease the accidents. One of many reasons to know the causes is with system dynamics, simulating the events of the Pedestrian behavior when accidents occur in risen cities. The implementation simulation joint with technology and research looking for saving lives, reducing the accidental rate, and to implementing or suggesting new policies from the government. This project is looking for the implementation of technology in video records and Deep Learning analysis for the service of the citizens, where a simulation model will be revealing the main variables which intervene in the pedestrian’s behavior. As initials results, shows the methodology here implemented, can reach data which was insufficient before thanks to the cameras and software of objects detection, those are the data input for the simulation model, which after to implement a change in a particular spot of Bucaramanga is possible to decrease the accident rate in 80% where pedestrians could be involved.

PhD Defence: “High-level synthesis and arithmetic optimizations”, Yohann Uguen, Chappe Amphitheater, CITI, 13th of November 2019 at 13h30

Title

High-level synthesis and arithmetic optimizations

Abstract

High-level synthesis (HLS) tools offer increased productivity regarding FPGA programming. However, due to their relatively young nature, they still lack many arithmetic optimizations. This thesis proposes safe arithmetic optimizations that should always be applied. These optimizations are simple operator specializations, following the C semantic. Other require to a lift the semantic embedded in high-level input program languages, which are inherited from software programming, for an improved accuracy/cost/performance ratio. To demonstrate this claim, the sum-of-product of floating-point numbers is used as a case study. The sum is performed on a fixed-point format, which is tailored to the application, according to the context in which the operator is instantiated.

In some cases, there is not enough information about the input data to tailor the fixed-point accumulator. The fall-back strategy used in this thesis is to generate an accumulator covering the entire floating-point range. This thesis explores different strategies for implementing such a large accumulator, including new ones. The use of a 2’s complement representation instead of a sign+magnitude is demonstrated to save resources and to reduce the accumulation loop delay.

Based on a tapered precision scheme and an exact accumulator, the posit number systems claims to be a candidate to replace the IEEE floating-point format. A throughout analysis of posit operators is performed, using the same level of hardware optimization as state-of-the-art floating-point operators. Their cost remains much higher that their floating-point counterparts in terms of resource usage and performance.

Finally, this thesis presents a compatibility layer for HLS tools that allows one code to be deployed on multiple tools. This library implements a strongly typed custom size integer type along side a set of optimized custom operators.

Jury

Philippe Coussy, Professeur des Universités, UBS, Lorient, France : Rapporteur
Olivier Sentieys, Professeur des Universités, Univ. Rennes, Inria, IRISA, Rennes : Rapporteur
Laure Gonnord, Maître de conférence, Université Lyon 1, France : Examinatrice
Frédéric Pétrot, Professeur des Universités, TIMA, Grenoble, France : Examinateur
Martin Kumm, Professeur des Universités, Université de Fulda, Allemagne : Examinateur
Florent de Dinechin, Professeur des Universités, INSA Lyon, France : Directeur de thèse