Publications

2017

• Energy efficient resource allocation for HARQ with statistical CSI in multiuser ad hoc networks
  
  • Leturc Xavier
  • Le Martret C.
  • Ciblat Philippe
  , 2017.
• Quantum protocols within Spekkens' toy model
  
  • Disilvestro Leonardo
  • Markham Damian
  Physical Review A : Atomic, molecular, and optical physics [1990-2015], American Physical Society, 2017, 95 (5). Quantum mechanics is known to provide significant improvements in information processing tasks when compared to classical models. These advantages range from computational speeds-up to security improvements. A key question is where these advantages come from. The toy model developed by Spekkens [R. W. Spekkens PRA 75, 032110 (2012)] mimics many of the features of quantum mechanics, such as entanglement and no-cloning, regarded as being important in this regard, despite being a local hidden variable theory. In this work we study several protocols within Spekkens' toy model where we see it can also mimic the advantages and limitations shown in the quantum case. We first provide explicit proofs for the impossibility of toy bit-commitment and the existence of a toy error correction protocol and consequent $k-$threshold secret sharing. Then, defining a toy computational model based on the quantum one-way computer we prove the existence of blind and verified protocols. Importantly, these two last quantum protocols are known to achieve a better-than-classical security. Our results suggest that such quantum improvements need not arise from any Bell-type non locality or contextuality, but rather as a consequence of steering correlations. (10.1103/PhysRevA.95.052324)
  DOI : 10.1103/PhysRevA.95.052324
• Narrow Linewidth Quantum Dot distributed Feedback Lasers
  
  • Duan Jianan
  • Huang Heming
  • Schires Kevin
  • Lu Zhaoyang
  • Poole Philip
  • Grillot Frédéric
  , 2017.
• Bernoulli Rank-1 Bandits for Click Feedback
  
  • Szepesvari Csaba
  • Kveton Bratislav
  • Katariya Sumeet
  • Vernade Claire
  , 2017.
• CODECAST: An Innovative Technology to Facilitate Teaching and Learning Computer Programming in a C Language Online Course
  
  • Sharrock Rémi
  • Ella Hamonic
  • Hiron Mathias
  • Carlier Sebastien
  , 2017. This paper introduces the CODECAST tool: an in-browser C language interpreter, paired with an event and voice recorder and player that facilitates teaching and learning to program by synchronizing audio with source code edition, visualization, step by step execution and testing. (10.1145/3051457.3053970)
  DOI : 10.1145/3051457.3053970
• Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere
  
  • Thomas Albert
  • Clémençon Stéphan
  • Gramfort Alexandre
  • Anne Sabourin
  , 2017, 54. Extreme regions in the feature space are of particular concern for anomaly detection: anomalies are likely to be located in the tails, whereas data scarcity in such regions makes it difficult to distinguish between large normal instances and anomalies. This paper presents an unsupervised algorithm for anomaly detection in extreme regions. We propose a Minimum Volume set (MV-set) approach relying on multivariate extreme value theory. This framework includes a canonical pre-processing step, which addresses the issue of output sensitivity to standardization choices. The resulting data representation on the sphere highlights the dependence structure of the extremal observations. Anomaly detection is then cast as a MV-set estimation problem on the sphere, where volume is measured by the spherical measure and mass refers to the angular measure. An anomaly then corresponds to an unusual observation given that one of its variables is large. A preliminary rate bound analysis is carried out for the learning method we introduce and its computational advantages are discussed and illustrated by numerical experiments.
• Increasing Public Value through Co-Creation of Open Knowledge
  
  • Andriessen Jerry
  • Baker Michael
  • Cordasco Gennaro
  • Donato Rosario
  • Malandrino Delfina
  • Palmieri Giovannella
  • Pardijs Mirjam
  • Petta Andrea
  • Pirozzi D.
  • Scarano Vittorio
  , 2017.
• Reducing Data Acquisition for Fast Structured Illumination Microscopy using Compressed Sensing
  
  • Meiniel William
  • Spinicelli Piernicola
  • Angelini Elsa
  • Fragola Alexandra
  • Loriette Vincent
  • Orieux François
  • Sepulveda Eduardo
  • Olivo-Marin Jean-Christophe
  , 2017. In this work, we introduce an original strategy to apply the Compressed Sensing (CS) framework to a super-resolution Structured Illumination Microscopy (SIM) technique. We first define a framework for direct domain CS, that exploits the sparsity of fluorescence microscopy images in the Fourier domain. We then propose an application of this method to a fast 4-images SIM technique, which allows to reconstruct super-resolved fluorescence microscopy images using only 25% of the camera pixels for each acquisition. (10.1109/isbi.2017.7950461)
  DOI : 10.1109/isbi.2017.7950461
• Codes for Side-Channel Attacks and Protections
  
  • Guilley Sylvain
  • Heuser Annelie
  • Rioul Olivier
  , 2017, 10194, pp.35-55. This article revisits side-channel analysis from the standpoint of coding theory. On the one hand, the attacker is shown to apply an optimal decoding algorithm in order to recover the secret key from the analysis of the side-channel. On the other hand, the side-channel protections are presented as a coding problem where the information is mixed with randomness to weaken as much as possible the sensitive information leaked into the side-channel. Therefore, the field of side-channel analysis is viewed as a struggle between a coder and a decoder. In this paper, we focus on the main results obtained through this analysis. In terms of attacks, we discuss optimal strategy in various practical contexts, such as type of noise, dimensionality of the leakage and of the model, etc. Regarding countermeasures, we give a formal analysis of some masking schemes, including enhancements based on codes contributed via fruitful collaborations with Claude Carlet. (10.1007/978-3-319-55589-8_3)
  DOI : 10.1007/978-3-319-55589-8_3
• Accelerating data preparation for big data analytics
  
  • Tian Yongchao
  , 2017. We are living in a big data world, where data is being generated in high volume, high velocity and high variety. Big data brings enormous values and benefits, so that data analytics has become a critically important driver of business success across all sectors. However, if the data is not analyzed fast enough, the benefits of big data will be limited or even lost. Despite the existence of many modern large-scale data analysis systems, data preparation which is the most time-consuming process in data analytics has not received sufficient attention yet. In this thesis, we study the problem of how to accelerate data preparation for big data analytics. In particular, we focus on two major data preparation steps, data loading and data cleaning. As the first contribution of this thesis, we design DiNoDB, a SQL-on-Hadoop system which achieves interactive-speed query execution without requiring data loading. Modern applications involve heavy batch processing jobs over large volume of data and at the same time require efficient ad-hoc interactive analytics on temporary data generated in batch processing jobs. Existing solutions largely ignore the synergy between these two aspects, requiring to load the entire temporary dataset to achieve interactive queries. In contrast, DiNoDB avoids the expensive data loading and transformation phase. The key innovation of DiNoDB is to piggyback on the batch processing phase the creation of metadata, that DiNoDB exploits to expedite the interactive queries. The second contribution is a distributed stream data cleaning system, called Bleach. Existing scalable data cleaning approaches rely on batch processing to improve data quality, which are very time-consuming in nature. We target at stream data cleaning in which data is cleaned incrementally in real-time. Bleach is the first qualitative stream data cleaning system, which achieves both real-time violation detection and data repair on a dirty data stream. It relies on efficient, compact and distributed data structures to maintain the necessary state to clean data, and also supports rule dynamics. We demonstrate that the two resulting systems, DiNoDB and Bleach, both of which achieve excellent performance compared to state-of-the-art approaches in our experimental evaluations, and can help data scientists significantly reduce their time spent on data preparation.
• Optimization of wireless sensor networks deployment with coverage and connectivity constraints
  
  • Elloumi Sourour
  • Hudry Olivier
  • Marie Estel
  • Plateau Agnès
  • Rovedakis Stephane
  , 2017, pp.0336-0341. (10.1109/CoDIT.2017.8102614)
  DOI : 10.1109/CoDIT.2017.8102614
• Constraints on photonic crystal fibers homogeneity for photon pair generation
  
  • Harlé Thibault
  • Barbier Margaux
  • Cordier Martin
  • Orieux Adeline
  • Diamanti Eleni
  • Zaquine Isabelle
  • Delaye Philippe
  , 2017, pp.QT6A.19. (10.1364/QIM.2017.QT6A.19)
  DOI : 10.1364/QIM.2017.QT6A.19
• Multi-User Quantum Key Distribution With Entangled Photons From A Semiconductor Chip
  
  • Autebert Claire
  • Diamanti Eleni
  • Ducci Sara
  • Gomez-Carbonnel Carme
  • Lemaître Aristide
  • Orieux Adeline
  • Trapateau Julien
  • Zaquine Isabelle
  , 2017, pp.QT6A.20. We demonstrate multi-user entanglement-based quantum key distribution using a AlGaAs chip emitting polarization entangled photon pairs at telecom wavelength and a standard dense wavelength division demultiplexer. (10.1364/QIM.2017.QT6A.20)
  DOI : 10.1364/QIM.2017.QT6A.20
• Liquid Filled Photonic Crystal Fiber : A Flexible Tool For Fibered Photon-Pair Generation
  
  • Cordier Martin
  • Orieux Adeline
  • Gabet Renaud
  • Harlé Thibault
  • Dubreuil Nicolas
  • Diamanti Eleni
  • Delaye Philippe
  • Zaquine Isabelle
  , 2017, pp.QW3C.5. (10.1364/QIM.2017.QW3C.5)
  DOI : 10.1364/QIM.2017.QW3C.5
• Webstrates for the Future Web?
  
  • Antonsen Kristian B
  • Beaudouin-Lafon Michel
  • Eagan James
  • Klokmose Clemens Nylandsted
  • Mackay Wendy
  • Rädle Roman
  , 2017, pp.1. Webstrates presents an alternative take on the future of web use and development. In Webstrates, changes to the Document Object Model (DOM) of webpages (called webstrates) are persisted across reloads and synchronized to other clients of the same webstrate. This includes changes to embedded JavaScript and CSS. With Webstrates we demonstrate one possible direction for the future web that we hope can inspire and foster discussion at the ProWeb 2017 workshop. We will gladly demonstrate Webstrates at the workshop and illustrate best programming practices for it. Further, we would like to discuss open issues (e.g. programming language support, collaborative programming, fine-grained permis- sions, handling large datasets, and other advances in the future of web programming) from which we believe future versions of Webstrates and its community will greatly benefit.
• Feature selection for an improved Parkinson's disease identification based on handwriting
  
  • Taleb Catherine
  • Likforman-Sulem Laurence
  • Khachab Maha
  • Mokbel Chafic
  , 2017, pp.52-56. Parkinson's disease (PD) is a neurological disorder associated with a progressive decline in motor skills, speech, and cognitive processes. Since the diagnosis of Parkinson's disease is difficult, researchers have worked to develop a support tool based on algorithms to differentiate healthy controls from PD patients. Online handwriting analysis is one of the methods that can be used to diagnose PD. The aim of this study is to find a subset of handwriting features suitable for efficiently identifying subjects with PD. Data was taken from PDMultiMC database collected in Lebanon, and consisting of 16 medicated PD patients and 16 age matched controls. Seven handwriting tasks were collected such as copying patterns, copying words in Arabic, and writing full names. For each task kinematic and spatio-temporal, pressure, energy, entropy, and intrinsic features were extracted. Feature selection was done in two stages, the first stage selected a subset using statistical analysis, and the second step select the most relevant features of this subset, by a suboptimal approach. The selected features were fed to a support vector machine classifier with RBF kernel, whose aim is to identify the subjects suffering from PD. The accuracy of the classification of PD was as high as 96.875%, with sensitivity and specificity equal to 93.75 % and 100%. The results as well as the selected features suggest that handwriting can be a valuable marker as a diagnosis tool. (10.1109/ASAR.2017.8067759)
  DOI : 10.1109/ASAR.2017.8067759
• Extended Selective Encryption of H.264/AVC (CABAC) and HEVC encoded video streams
  
  • Boyadjis Benoit
  • Bergeron Cyril
  • Pesquet-Popescu Beatrice
  • Dufaux Frederic
  IEEE Transactions on Circuits and Systems for Video Technology, Institute of Electrical and Electronics Engineers, 2017, 27 (4), pp.892-906. This paper proposes an extended Selective Encryption (SE) method for both H.264/AVC (CABAC) and HEVC streams. Namely, this work addresses the main security issue that SE is facing : the content protection, related to the amount of information leakage through a protected video. Our contribution is the improvement of the visual distortion induced by SE approaches. If previous works on both H.264/AVC (CABAC) and HEVC limit encryption to bins treated by one specific mode of CABAC: its by-pass mode - which has the advantage of preserving the overall bitrate -, we propose here to also rely on the encryption of the more widely used mode of CABAC: its regular mode. This allows to encrypt a major codeword for video reconstruction : the prediction modes for Intra blocks/units. Disturbing their statistics may cause bitrate overhead, which is the trade-off for improving the content security level of the SE approach. A comprehensive study of this compromise between the improvement of the scrambling efficiency and the undesirable aftereffects is proposed in this paper, and a specific security analysis of the proposed CABAC regular mode encryption is conducted. (10.1109/TCSVT.2015.2511879)
  DOI : 10.1109/TCSVT.2015.2511879
• Three tools to learn C programming online
  
  • Sharrock Rémi
  , 2017.
• Vidéo-ethnographie des usages de Gallica
  
  • Rollet Nicolas
  • Beaudouin Valérie
  • Garron Isabelle
  , 2017. Ces dernières années, les interfaces d’accès aux collections numériques des bibliothèques patrimoniales ont vu leur audience croître en même temps que le nombre et la diversité des documents mis à disposition. Qui sont les utilisateurs de ces collections ? Comment les découvrent-ils et les utilisent-ils, selon quelle logique d’interrogation avec quels effets sur la connaissance ? Pour répondre à ces questions, un projet de recherche de 10 mois (2016-2017) a été conduit par la Bibliothèque nationale de France, le labex Obvil et Télécom ParisTech : "Mettre en ligne le patrimoine : évolution des usages, transformation des savoirs ?" À travers l’exemple de Gallica, bibliothèque numérique de la BnF et de ses partenaires, il s’agissait d’analyser l’évolution des usages des collections patrimoniales numérisées, en particulier la manière dont celles-ci sont perçues et intégrées dans des stratégies de recherche, professionnelles et amateurs. L’étude vidéo-ethnographique constitue le deuxième volet du projet de recherche. L’objectif est d’observer au plus près les parcours des utilisateurs et les spécificités de leurs pratiques en ligne. La captation audiovisuelle de l’activité à l’écran est complétée par des entretiens d’autoconfrontation qui permettent de donner sens aux observations. Deux axes d’analyse découlent des données recueillies. Le premier porte sur les phénomènes de catégorisation et d’évaluation (d’une liste de résultats, d’un document) et souligne la façon dont une idée, guidée par des motifs et dynamisée par de la sérendipité, peut émerger et se configurer dans le temps de la consultation. Le second explore la dimension écologique de l’usage de Gallica. Il met en lumière que l’utilisateur de Gallica est engagé dans de nombreuses opérations structurantes associant environnement numérique, matériel et social.
• Raisonnement abductif en logique de description exploitant les domaines concrets spatiaux pour l'inteprétation d'images
  
  • Yang Yifan
  • Atif J.
  • Bloch Isabelle
  Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2017, 1-2, pp.11-39. L’interprétation d’images a pour objectif non seulement de détecter et reconnaître des objets dans une scène mais aussi de fournir une description sémantique tenant compte des in- formations contextuelles dans toute la scène. Le problème de l’interprétation d’images peut être formalisé comme un problème de raisonnement abductif, c’est-à-dire comme la recherche de la meilleure explication en utilisant une base de connaissances. Dans ce travail, nous présentons une nouvelle approche utilisant une méthode par tableau pour la génération et la sélection d’explications possibles d’une image donnée lorsque les connaissances, exprimées dans une logique de description, comportent des concepts décrivant les objets mais aussi les relations spatiales entre ces objets. La meilleure explication est sélectionnée en exploitant les domaines concrets pour évaluer le degré de satisfaction des relations spatiales entre les objets.
• Incentive-oriented Task Assignment in Holonic Organic Systems
  
  • Kantert Jan
  • Tomforde Sven
  • Diaconescu Ada
  • Müller-Schloer Christian
  , 2017.
• Integration of learning tools using LTI on edX
  
  • Sharrock Rémi
  , 2017.
• On a generalised combinatorial conjecture involving addition mod 2^k -1
  
  • Flori Jean-Pierre
  • Cohen Gérard
  Int. J. Information and Coding Theory, 2017, 4 (2/3), pp.107-115.
• Fast algebraic immunity of Boolean functions
  
  • Mesnager Sihem
  • Cohen Gérard
  Advances in Mathematics of Communications, AIMS, 2017, 11 (2), pp.373-377.
• Codecast: a step-by-step online execution tool to learn how to program in C
  
  • Sharrock Rémi
  • Hamonic Ella
  , 2017.