Publications

2017

• Accelerated encryption algorithms for secure storage and processing in the cloud
  
  • Badii Atta
  • Faulkner Ryan
  • Glackin Cornelius
  • Chollet Gérard
  , 2017, pp.1-6. The objective of this paper is to outline the design specification, implementation and evaluation of a proposed accelerated encryption framework which deploys both homomorphic and symmetric-key encryptions to serve the privacy preserving processing; in particular, as a sub-system within the Privacy Preserving Speech Processing framework architecture as part of the PPSP-in-Cloud Platform. Following a preliminary study of GPU efficiency gains optimisations benchmarked for AES implementation we have addressed and resolved the Big Integer processing challenges in parallel implementation of bilinear pairing thus enabling the creation of partially homomorphic encryption schemes which facilitates applications such as speech processing in the encrypted domain on the cloud. This novel implementation has been validated in laboratory tests using a standard speech corpus and can be used for other …
• Optimal distributed channel assignment in D2D networks using learning in noisy potential games
  
  • Ali Mohammed Shabbir
  • Coucheney Pierre
  • Coupechoux Marceau
  , 2017, pp.151-156. (10.1109/INFCOMW.2017.8116368)
  DOI : 10.1109/INFCOMW.2017.8116368
• Superstrat tout diélectrique pour le contrôle du rayonnement d’une antenne – Prototypage et mesures
  
  • Joshi Chetan
  • Lepage A. C.
  • Begaud Xavier
  • Piau Gérard-Pascal
  , 2017.
• Energy efficient resource allocation for HARQ with statistical CSI in multiuser ad hoc networks
  
  • Leturc Xavier
  • Le Martret C.
  • Ciblat Philippe
  , 2017.
• 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.
• 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
• 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.
• 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
• 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
• 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
• 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
• 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
• 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.
• An experimental analysis of Noise-Contrastive Estimation: the noise distribution matters
  
  • Labeau Matthieu
  • Allauzen Alexandre
  , 2017, pp.15 - 20. Noise Contrastive Estimation (NCE) is a learning procedure that is regularly used to train neural language models, since it avoids the computational bottleneck caused by the output softmax. In this paper , we attempt to explain some of the weaknesses of this objective function, and to draw directions for further developments. Experiments on a small task show the issues raised by the unigram noise distribution, and that a context dependent noise distribution, such as the bigram distribution , can solve these issues and provide stable and data-efficient learning.
• Slope-assistedBOTDR for pipeline vibration measurements
  
  • Maraval Damien
  • Gabet Renaud
  • Jaouën Yves
  • Lamour Vincent
  , 2017, pp.paper 10323-56.
• From Photon to Pixel: The digital camera
  
  • Maître Henri
  , 2017.
• Codecast: a step-by-step online execution tool to learn how to program in C
  
  • Sharrock Rémi
  • Hamonic Ella
  , 2017.
• Fast algebraic immunity of Boolean functions
  
  • Mesnager Sihem
  • Cohen Gérard
  Advances in Mathematics of Communications, AIMS, 2017, 11 (2), pp.373-377.
• The Web, the Users, and the MOS: Influence of HTTP/2 on User Experience
  
  • Bocchi Enrico
  • de Cicco Luca
  • Mellia M.
  • Rossi Dario
  , 2017. <p>This work focuses on the evaluation of Web quality of experience as perceived by actual users and in particular on the impact of HTTP/1 vs HTTP/2. We adopt an experimental methodology that uses real web pages served through a realistic testbed where we control network, protocol, and application configuration. Users are asked to browse such pages and provide their subjective feedback, which we leverage to obtain the Mean Opinion Score (MOS), while the testbed records objective metrics.</p> <p> </p> <p>The collected dataset comprises over 4,000 grades that we explore to tackle the question whether HTTP/2 improves users experience, to what extent, and in which conditions. Findings show that users report marginal differences, with 22\%, 52\%, 26\% of HTTP/2 MOS being better, identical, or worse than HTTP/1, respectively. Even in scenarios that favor HTTP/2, results are not as sharp as expected. This is in contrast with objective metrics, which instead record a positive impact with HTTP/2 usage. This shows the complexity of understanding the web experience and the need to involve actual users in the quality assessment process.</p>
• 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.