Publications

2020

• Resilience by design & failures forecasting for a connected autonomous vehicle
  
  • Monteuuis Jean-Philippe
  , 2020. Autonomous vehicles with an automation level 5 will drive autonomously in any road scenarios such as highways, snowy roads, urban areas, or traffic jams. The integration of V2X communication, as a new source of perception for the vehicle could remove the limitations of local perception by communicating with an occluded pedestrian or by detecting in advance the presence of a vehicle under a heavy mist. However, this V2X communication may be a new source of attacks threatening the vehicle perception. Current countermeasures are not designed for all autonomous vehicles because these countermeasures require the driver assistance or work with a specific set of sensors. Therefore, the thesis aims to propose a generic failure resilient perception architecture for all types of connected and autonomous vehicles supporting different kinds of sensors. In this thesis, we propose a generic perception architecture named GPA with its failure resilient perception algorithm (FRPA). We propose a new threat analysis and risk assessment method named SARA that identifies and assess the risk of attacks targeting connected and automated vehicles with an automation level 5. To identify where and how these attacks occur, we propose an attacker and a security goal model for all automotive perception systems. We implemented two modules of our failures resilient perception algorithm (FRPA): a Machine Learning based Failure Classifier and a V2X-Sensor Correlation Module considering three kinds of source: camera, radar, and V2X. We highlighted several new attacks in the perception pipeline and raise the need for new security countermeasures such as the physical integrity of road infrastructures and trustworthy perception algorithms. Besides, our countermeasures based on machine learning and sensor correlation showed very accurate results to detect and classifies perception failures (over 90% accuracy score). Finally, the ideas developed in the thesis resulted in 10 filled patents and several publications. (10.70675/5bb4affaz6191z4303za083ze77ca86299b8)
  DOI : 10.70675/5bb4affaz6191z4303za083ze77ca86299b8
• Full-duplex for cellular networks : a stochastic geometry approach
  
  • Arrano Scharager Hernan
  , 2020. Full-duplex (FD) is a principle in which a transceiver can receive and transmit on the same time-frequency radio resource. The principle was long held as impractical due to the high self-interference that arises when simultaneously transmitting and receiving in the same resource block. When assuming perfect self-interference cancellation, FD can potentially double the spectral efficiency (SE) of a given point-to-point communication. In practice though, it is not possible to achieve the aforementioned characteristic. Moreover, under a cellular network context, not only the self-interference limits the performance, since additional co-channel interference is created by base stations (BSs) and users equipment (UEs). However, even with the higher interference dowlinks (DLs) still obtain higher SE performances, whereas uplinks (ULs) are generally critically degraded, when compared to half-duplex (HD). We focus our work in the study of alternatives that can help improve the impaired ULs in FD networks, while still trying to profit from the gains experienced by DLs.In this regard, we use stochastic geometry along the thesis as a means to characterize key performance indicators of cellular networks, such as: coverage probability, average SE and data rates. The thesis is divided into three major studies. Firstly, we propose a duplex-switching policy which enables BSs to operate in FD- or HD- depending on the UL and DL conditions. Secondly, we investigate the performance of hybrid HD/FD networks under a millimeter wave context. Finally, we propose a novel algorithm based on nonorthogonal multiple-access (NOMA) and successive interference cancellation (SIC), which allows BSs to coordinate on their respective transmission schemes to reduce the BS-to-BS interference. We demonstrate that the models presented in the thesis allow to balance the gains of one link over the other; reducing the UL degradation, while maintaining DL gains. In addition, we show that scenarios in which equipment is able to perform beamforming are ideal for FD deployments, since they directly reduce the cochannel interference. (10.70675/6cd908c0z3795z478az87a9z8bc7ae0a1431)
  DOI : 10.70675/6cd908c0z3795z478az87a9z8bc7ae0a1431
• Engineering Railway Systems with an Architecture-Centric Process Supported by AADL and ALISA: an Experience Report
  
  • Crisafulli Paolo
  • Blouin Dominique
  • Caron Françoise
  • Maxim Cristian
  , 2020. The increasing automation of transportation systems has contributed to the emergence of the so-called Cyber-Physical Systems (CPS), which are computation-based systems in which computing devices, sensors, actuators and networks collaborate to monitor and control physical entities via feedback loops. To cope with the increasing complexity of such systems, engineering teams require model-based tools, because they can provide early virtual integration and verification, reuse of existing models, requirements traceability and support of an incremental development process. However, these benefits can only be earned if the chosen modelling languages are expressive enough to capture all aspects necessary to perform the virtual verifications with the required confidence degree.
• Towards Formal Verification of Autonomous Driving Supervisor Functions
  
  • Assioua Yasmine
  • Ameur-Boulifa Rabéa
  • Guitton-Ouhamou Patricia
  , 2020. In the software development lifecycle, errors and flaws can be introduced in the different phases and lead to failures. Establishing a set of functional requirements helps producing safe software. However, ensuring that the (being) developed software is compliant with those requirements is a challenging task due to the lack of automatic and formal means to lead this verification. In this paper, we present our approach that aims at analysing a collection of automotive requirements by using formal methods. The proposed approach for formal verification is evaluated by the application to supervisor functions of the autonomous driving (AD) system, the system in charge of self-driving.
• Hardware / Software / Analog System Partitioning with SysML and SystemC-AMS
  
  • Genius Daniela
  • Apvrille Ludovic
  , 2020. Model-driven approaches for designing software and hardware parts of embedded systems are generally limited to their digital parts. On the other hand, virtual prototyping and co-simulation have emerged as a promising research topic, but target the modeling levels when partitioning has already been performed. This paper presents a model-driven platform for the partitioning of analog/mixed-signal systems. keywords: virtual prototyping, embedded systems , analog/mixed signal, design space exploration
• A New Network Configuration Management Architecture for Future Aircraft Systems
  
  • Delmas Thibault
  • Iannone Luigi
  • Garcia Jean-Pierre
  • Monsuez Bruno
  , 2020. Aircraft systems are evolving and being enhanced thanks to new design paradigms leveraging on recent technology advances in embedded systems. However, the Integrated Modular Avionics (IMA) model, used in current avionics, has shown important limitations to accommodate such evolution. These new paradigms demand for much more global system modularity than what IMA is able to offer. Such system evolution has as well an impact on the underlying different networks present on aircrafts. In this context, it is mandatory to investigate the kind and the breadth of adaptation networks need in order to cope with new requirements. To this end, this paper we firstly investigate the current aircrafts network configuration and management procedures. It appears that they lack the features, more specifically, the configuration management features, necessary to support these new use cases. We then look at proposals trying to fulfil this features gap. Each of them, while providing parts of the answers, also come with trade-off or insufficiencies that prevent them from fully answering to the new needs. Then, a new network configuration architecture able to cope with the newly defined configuration management requirements is provided. A comparison to the other approaches is presented, so to highlight how the proposed architecture better fulfils long-term evolution requirements while being less complex and more suitable for current configuration procedures than the other proposal. Finally, a simulation of the configuration architecture is done to provide insights on the new proposed features.
• Invited Lecture on Continous-Variable Quantum Key Distribution
  
  • Alleaume Romain
  , 2020.
• Prédiction conformelle profonde pour des modèles robustes
  
  • Messoudi Soundouss
  • Rousseau Sylvain
  • Destercke Sébastien
  , 2020, RNTI-E-36, pp.301-308. Les réseaux profonds, comme d'autres modèles, peuvent associer une confiance élevée à des prédictions peu fiables. Rendre ces modèles robustes et fiables est donc essentiel, surtout pour les décisions critiques. Ce papier montre expérimentalement que la prédiction conformelle, et plus particulièrement l'ap-proche de [Hechtlinger et al. (2018)], apporte une solution convaincante à ce défi. La prédiction conformelle fournit un ensemble de classes couvrant la vraie classe avec avec une fréquence choisie au préalable par l'utilisateur. Dans le cas où l'exemple à prédire est atypique, la prédiction conformelle prédira l'en-semble vide. Les expériences menées montrent le bon comportement de l'ap-proche conformelle, en particulier lorsque les données sont bruitées.
• High Security Bare Metal Bluetooth Blockchain Payment Terminal For Trusted Ethereum Transaction
  
  • Urien Pascal
  , 2020, pp.1-2. (10.1109/CCNC46108.2020.9045146)
  DOI : 10.1109/CCNC46108.2020.9045146
• Innovative ATMEGA8 Microcontroler Static Authentication Based on SRAM PUF
  
  • Urien Pascal
  , 2020, pp.1-2. (10.1109/CCNC46108.2020.9045502)
  DOI : 10.1109/CCNC46108.2020.9045502
• On the Effect of Aging on Digital Sensors
  
  • Anik Md Toufiq Hasan
  • Guilley Sylvain
  • Danger Jean-Luc
  • Karimi Naghmeh
  , 2020, pp.189-194. (10.1109/VLSID49098.2020.00050)
  DOI : 10.1109/VLSID49098.2020.00050
• Static Data-Flow Analysis of UML/SysML Functional Views for Signal and Image Processing Applications
  
  • Enrici Andrea
  • Apvrille Ludovic
  • Pacalet Renaud
  • Pham Minh Hiep
  , 2020, pp.101-126. (10.1007/978-3-030-37873-8_5)
  DOI : 10.1007/978-3-030-37873-8_5
• Nonparametric imputation by data depth
  
  • Mozharovskyi Pavlo
  • Josse Julie
  • Husson François
  Journal of the American Statistical Association, Taylor & Francis, 2020, 115 (529), pp.241-253. The presented methodology for single imputation of missing values borrows the idea from data depth --- a measure of centrality defined for an arbitrary point of the space with respect to a probability distribution or a data cloud. This consists in iterative maximization of the depth of each observation with missing values, and can be employed with any properly defined statistical depth function. On each single iteration, imputation is narrowed down to optimization of quadratic, linear, or quasiconcave function being solved analytically, by linear programming, or the Nelder-Mead method, respectively. Being able to grasp the underlying data topology, the procedure is distribution free, allows to impute close to the data, preserves prediction possibilities different to local imputation methods (k-nearest neighbors, random forest), and has attractive robustness and asymptotic properties under elliptical symmetry. It is shown that its particular case --- when using Mahalanobis depth --- has direct connection to well known treatments for multivariate normal model, such as iterated regression or regularized PCA. The methodology is extended to the multiple imputation for data stemming from an elliptically symmetric distribution. Simulation and real data studies positively contrast the procedure with existing popular alternatives. The method has been implemented as an R-package. (10.1080/01621459.2018.1543123)
  DOI : 10.1080/01621459.2018.1543123
• An Indirect Determination of the Polarization Anisotropy in a Quantum Cascade Laser Under Strong Cross-Polarization Feedback
  
  • Spitz O
  • Herdt A
  • Carras M
  • Maisons G
  • Elsässer W
  • Grillot F
  , 2020. This work demonstrates that a non TM-polarized wave can be generated by a quantum cascade laser subjected to strong cross-polarization optical feedback. This finding is used to determine the anisotropy between the two existing polarizations Acknowledgments: this work is supported by the French Defense Agency (DGA), the French ANR program under grant ANR-17-ASMA-0006
• From formal test objectives to TTCN-3 for verifying ETCS complex software control systems
  
  • Ameur-Boulifa Rabéa
  • Cavalli Ana R
  • Maag Stephane
  , 2020, 1250, pp.156-178. The design of a practical but accurate software methodology to guarantee systems correctness and safety is still a big challenge. Where test coverage is dissatisfying, formal analysis grants much higher potential to discover errors or safety vulnerabilities during the design phase of a system. However, formal verification methods often require a strong technical background that limits their usage. In this paper, we present a framework based on testing and verification to ensure the correctness and safety of complex distributed software systems. As a result of the application of our methodology we obtain a more reliable system, in terms of functionality, safety and robustness and a reduction of the time necessary for verification. In order to show the applicability of our solution we applied it on a real industrial case study, that is the European Train Control System (ETCS) [14]. We specify the system using the SDL language [24], and we use a test generation tool to generate abstract test cases in TTCN-3. Based on these standardized tests, we verify using model-checking, some critical properties of the system, in particular these regarding safety requirements. We analyse a real train accident and we demonstrate how the accident could have been avoided if the ETCS system was used. (10.1007/978-3-030-52991-8_8)
  DOI : 10.1007/978-3-030-52991-8_8
• CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer
  
  • Kips R.
  • Perrot M.
  • Gori P.
  • Bloch Isabelle
  , 2020.
• La mathématique migrante
  
  • Zayana Karim
  • Jadiba Sami
  • Kraiem Selma
  • Fayala Abdelwahid
  Les Cahiers Pédagogiques, 2020, 558. La route de l'inconnu(e) : histoire de quelques concepts mathématiques à travers les grandes migrations en méditerranée
• Simulation Framework for Misbehavior Detection in Vehicular Networks
  
  • Kamel Joseph
  • Raashid Ansari Mohammad
  • Petit Jonathan
  • Kaiser Arnaud
  • Ben Jemaa Ines
  • Urien Pascal
  IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers, 2020, 69 (6), pp.6631-6643. Cooperative Intelligent Transport Systems (C-ITS) is an ongoing technology that will change our driving experience in the near future. In such systems, vehicles and RoadSide Unit (RSU) cooperate by broadcasting V2X messages over the vehicular network. Safety applications use these data to detect and avoid dangerous situations on time. MisBehavior Detection (MBD) in C-ITS is an active research topic which consists of monitoring data semantics of the exchanged Vehicle-to-X communication (V2X) messages to detect and identify potential misbehaving entities. The detection process consists of performing plausibility and consistency checks on the received V2X messages. If an anomaly is detected, the entity may report it by sending a Misbehavior Report (MBR) to the Misbehavior Authority (MA). The MA will then investigate the event and decide to revoke the sender or not. In this paper, we present a MisBehavior Detection (MBD) simulation framework that enables the research community to develop, test, and compare MBD algorithms. We also demonstrate its capabilities by running example scenarios and discuss their results. Framework For Misbehavior Detection (F 2 MD) is open source and available for free on our github. (10.1109/TVT.2020.2984878)
  DOI : 10.1109/TVT.2020.2984878
• Constructions of optimal locally recoverable codes via Dickson polynomials.
  
  • Liu J.
  • Mesnager Sihem
  • Tang D.
  Journal of Designs, Codes, and Cryptography, 2020.
• Software Acceleration Techniques for High-speed Programmable Networks
  
  • Linguaglossa Leonardo
  , 2020, 6, pp.203-216. Network programmability has provided an effective approach to enable innovation in network systems. By replacing static, expensive middleboxes with equivalent pieces of software implementing the same functionality, operators can significantly reduce their CAPEX/OPEX expenditures, and engineers can rapidly design, test and deploy novel architectures and services, thus reducing the time-to-market for network applications. However, the flexibility provided by software solutions comes at a cost: purposespecific hardware has the clear advantage of optimized performance (i.e., throughput, latency) with respect to pure software-based solutions. The introduction of software acceleration techniques represented an essential step towards the increasing popularity of the SDN/NFV paradigm shift, by reducing the performance gap between hardware-based and software-based systems. Thanks to such techniques, modern software-networking solutions can operate at multi-10Gbps rate (up to hundreds of Gbps) on commodity servers equipped with regular COTS components. In this chapter, we cover the aspects related to software acceleration techniques in a bottom-up fashion: we first provide an overview of high-speed software networking on COTS architectures, and we then explore the evolution of softwarized networking by focusing on performance acceleration and the design space for high-speed programmable networks. (10.57620/CNIT-Report_06)
  DOI : 10.57620/CNIT-Report_06
• An Experimental Study of State-of-the-Art Entity Alignment Approaches
  
  • Zhao Xiang
  • Zeng Weixin
  • Tang Jiuyang
  • Wang​ Wei
  • Suchanek Fabian
  IEEE Transactions on Knowledge and Data Engineering, Institute of Electrical and Electronics Engineers, 2020. Entity alignment (EA) finds equivalent entities that are located in different knowledge graphs (KGs), which is an essential step to enhance the quality of KGs, and hence of significance to downstream applications (e.g., question answering and recommendation). Recent years have witnessed a rapid increase of EA approaches, yet the relative performance of them remains unclear, partly due to the incomplete empirical evaluations, as well as the fact that comparisons were carried out under different settings (i.e., datasets, information used as input, etc.). In this paper, we fill in the gap by conducting a comprehensive evaluation and detailed analysis of state-of-the-art EA approaches. We first propose a general EA framework that encompasses all the current methods, and then group existing methods into three major categories. Next, we judiciously evaluate these solutions on a wide range of use cases, based on their effectiveness, efficiency and robustness. Finally, we construct a new EA dataset to mirror the real-life challenges of alignment, which were largely overlooked by existing literature. This study strives to provide a clear picture of the strengths and weaknesses of current EA approaches, so as to inspire quality follow-up research. (10.1109/TKDE.2020.3018741)
  DOI : 10.1109/TKDE.2020.3018741
• Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
  
  • Şimşekli Umut
  • Zhu Lingjiong
  • Teh Yee Whye
  • Gürbüzbalaban Mert
  , 2020. Stochastic gradient descent with momentum (SGDm) is one of the most popular optimization algorithms in deep learning. While there is a rich theory of SGDm for convex problems, the theory is considerably less developed in the context of deep learning where the problem is non-convex and the gradient noise might exhibit a heavy-tailed behavior, as empirically observed in recent studies. In this study, we consider a \emph{continuous-time} variant of SGDm, known as the underdamped Langevin dynamics (ULD), and investigate its asymptotic properties under heavy-tailed perturbations. Supported by recent studies from statistical physics, we argue both theoretically and empirically that the heavy-tails of such perturbations can result in a bias even when the step-size is small, in the sense that \emph{the optima of stationary distribution} of the dynamics might not match \emph{the optima of the cost function to be optimized}. As a remedy, we develop a novel framework, which we coin as \emph{fractional} ULD (FULD), and prove that FULD targets the so-called Gibbs distribution, whose optima exactly match the optima of the original cost. We observe that the Euler discretization of FULD has noteworthy algorithmic similarities with \emph{natural gradient} methods and \emph{gradient clipping}, bringing a new perspective on understanding their role in deep learning. We support our theory with experiments conducted on a synthetic model and neural networks.
• Optimizing Inner Product Masking Scheme by A Coding Theory Approach
  
  • Cheng Wei
  • Guilley Sylvain
  • Carlet Claude
  • Mesnager Sihem
  • Danger Jean-Luc
  IEEE Transactions on Information Forensics and Security, Institute of Electrical and Electronics Engineers, 2020, 16, pp.220-235. Masking is one of the most popular countermeasures to protect cryptographic implementations against side-channel analysis since it is provably secure and can be deployed at the algorithm level. To strengthen the original Boolean masking scheme, several works have suggested using schemes with high algebraic complexity. The Inner Product Masking (IPM) is one of those. In this paper, we propose a unified framework to quantitatively assess the side-channel security of the IPM in a coding-theoretic approach. Specifically, starting from the expression of IPM in a coded form, we use two defining parameters of the code to characterize its side-channel resistance. In order to validate the framework, we then connect it to two leakage metrics (namely signal-to-noise ratio and mutual information, from an information-theoretic aspect) and one typical attack metric (success rate, from a practical aspect) to build a firm foundation for our framework. As an application, our results provide ultimate explanations on the observations made by Balasch et al. at EUROCRYPT'15 and at ASIACRYPT'17, Wang et al. at CARDIS'16 and Poussier et al. at CARDIS'17 regarding the parameter effects in IPM, like higher security order in bounded moment model. Furthermore, we show how to systematically choose optimal codes (in the sense of a concrete security level) to optimize IPM by using this framework. Eventually, we present a simple but effective algorithm for choosing optimal codes for IPM, which is of special interest for designers when selecting optimal parameters for IPM. (10.1109/TIFS.2020.3009609)
  DOI : 10.1109/TIFS.2020.3009609
• Constructions of self-orthogonal codes from hulls of BCH codes and their parameters
  
  • Du Z.
  • Li C.
  • Mesnager Sihem
  IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers, 2020.
• Recent results and problems on constructions of linear codes from cryptographic functions
  
  • Li N.
  • Mesnager Sihem
  Journal of Cryptography and Communications- Discrete Structures, Boolean Functions, and Sequences, 2020.