Publications

2017

• Identity-based cryptography (IBC) based key management system (KMS) for industrial control systems (ICS)
  
  • Drias Zakarya
  • Serhrouchni Ahmed
  • Vogel Olivier
  , 2017, pp.1-10. Often considered as the brain of an industrial process, Industrial control systems are presented as the vital part of today's critical infrastructure due to their crucial role in process control and monitoring. Any failure or error in the system will have a considerable damage. Their openness to the internet world raises the risk related to cyber-attacks. Therefore, it's necessary to consider cyber security challenges while designing an ICS in order to provide security services such as authentication, integrity, access control and secure communication channels. To implement such services, it's necessary to provide an efficient key management system (KMS) as an infrastructure for all cryptographic operations, while preserving the functional characteristics of ICS. In this paper we will analyze existing KMS and their suitability for ICS, then we propose a new KMS based on Identity Based Cryptography (IBC) as a better alternative to traditional KMS. In our proposal, we consider solving two security problems in IBC which brings it up to be more suitable for ICS. (10.1109/CSNET.2017.8242008)
  DOI : 10.1109/CSNET.2017.8242008
• Multilingual cyberbullying detection system: Detecting cyberbullying in Arabic content
  
  • Haidar Batoul
  • Chamoun Maroun
  • Serhrouchni Ahmed
  , 2017, pp.1-8. In the era of Internet and electronic devices bullying shifted its place from schools and backyards into the cyberspace; it is now known as Cyberbullying. Children of the Arab countries are suffering from cyberbullying same as children worldwide. Thus concerns from cyberbullying are elevating. A lot of research is done for the purpose of handling this situation. The current research is focusing on detection and mitigation of cyberbullying; while previous research dealt with the psychological effects of cyberbullying on the victim and the predator. A lot of research proposed solutions for detecting cyberbullying in English language and a few more languages, but none till now covered cyberbullying in Arabic language. Several techniques contribute in cyberbullying detection, mainly Machine Learning (ML) and Natural Language Processing (NLP). This paper presents a solution for detecting and stopping cyberbullying with focus on content written in Arabic Language. Thus the primary results of the system are displayed and discussed. (10.1109/CSNET.2017.8242005)
  DOI : 10.1109/CSNET.2017.8242005
• A Lightweight IoT Security Protocol
  
  • Hammi Mohamed Tahar
  • Livolant Erwan
  • Bellot Patrick
  • Serhrouchni Ahmed
  • Minet Pascale
  , 2017. The IoT is a technology that enables the inter-connection of smart physical and virtual objects and provides advanced services. Objects or things are generally constrained devices which are limited by their energy, computing and storage capacity. A Wireless Sensor Networks (WSN) is a network composed of devices managed by a CPAN (Personal Area Network Coordinator). The network is used in order to gather and process data of a given environment. It is characterized by their low bit rate and low power consumption, and it uses small size packet in their transmissions. In order to protect the WSN, a mutual authentication between devices is required during the association of a new device. The exchanged data should be authenticated and encrypted. In this work we propose a robust, lightweight and energy-efficient security protocol for the WSN systems. The real tests we made and a performance evaluation of our security protocol are provided.
• A study of norms in convex optimization super-resolution from compressed sources
  
  • Purica Andrei
  • Boyadjis Benoit
  • Pesquet-Popescu Béatrice
  • Dufaux Frederic
  , 2017. Advancements over the last decade in video acquisition and display technologies lead to a continuous increase of video content resolution. These aspects combined with the shift towards cloud multimedia services and the underway adoption of High Efficiency Video Coding standards (HEVC) create a lot of interest for Super-Resolution (SR) and video enhancing techniques. Recent works showed that proximal based convex optimization approaches provide a promising direction in video restoration. An important aspect in the definition of a SR model is the metric used in defining the objective function. Most techniques are based on the classical I2 norm. In this paper we further investigate the use of other norms and their behavior w.r.t. multiple quality evaluation metrics. We show that significant gains of up to 0.5 dB can be obtained when using different norms. (10.1109/mmsp.2017.8122216)
  DOI : 10.1109/mmsp.2017.8122216
• Statistical Analysis and Directional Coding of Layer-based HDR Image Coding Residue
  
  • Feyiz Kutan
  • Kamisli Fatih
  • Zerman Emin
  • Valenzise Giuseppe
  • Koz Alper
  • Dufaux Frederic
  , 2017. Existing methods for layer-based backward compatible high dynamic range (HDR) image and video coding mostly focus on the rate-distortion optimization of base layer while neglecting the encoding of the residue signal in the enhancement layer. Although some recent studies handle residue coding by designing function based fixed global mapping curves for 8-bit conversion and exploiting standard codecs on the resulting 8-bit images, they do not take the local characteristics of residue blocks into account. Inspired by the local anisotropic characteristics of the residue signal and directional methods for motion compensated low dynamic range (LDR) video coding, in this paper we first investigate whether HDR image coding residue exhibits also local anisotropic characteristics. Specifically, we verify directional structures in residue blocks by means of auto-covariance analysis for different bitrates, spatial activities and dynamic ranges as the main variables in HDR image coding. Then, we compare the rate distortion performances of directional coding methods with the baseline residue coding methods in the literature along with different combinations of 8-bit conversion methods. The experiments indicate that content dependent 8-bit conversions and directional coding significantly outperforms the existing function based 8-bit conversions and typical coding for residue coding. (10.1109/mmsp.2017.8122244)
  DOI : 10.1109/mmsp.2017.8122244
• Quality of Experience in UHD-1 Phase 2 television: the contribution of UHD+HFR technology
  
  • Hulusic Vedad
  • Valenzise Giuseppe
  • Fournier Jérôme
  • Gicquel Jean-Charles
  • Dufaux Frederic
  , 2017. A key factor to determine the quality of experience (QoE) of a video is its capability to convey the large spectrum of perceptual phenomena that our eyes can sense in real life. In order to meet this demand, the recent DVB UHD-1 Phase 2 specification employs new video features, such as higher spatial resolutions (4K/8K) and High Frame Rate (HFR). The first enables larger field of view and level of details, while the second offers sharper images of moving objects going well beyond the current frame rates. While the contribution of each of these technologies to QoE has been investigated individually, in this paper we are interested to study their interaction, and in quantifying the benefits to users from their combination. To this end, we conduct a subjective test on compressed UHD+HFR content on a recent display capable of reproducing 100 pictures per second at 2160p resolution, with the goal to assess the increase in QoE of UHD and HFR with respect to conventional video, both individually and in combination. The results indicate that for content with fast motion, at higher bitrates the combination of UHD and HFR significantly improves the QoE compared to that obtained when these features are used individually. (10.1109/mmsp.2017.8122238)
  DOI : 10.1109/mmsp.2017.8122238
• Possible and Certain Answers for Queries over Order-Incomplete Data
  
  • Amarilli Antoine
  • Lamine Ba Mouhamadou
  • Deutch Daniel
  • Senellart Pierre
  , 2017, 90, pp.4:1-4:19. To combine and query ordered data from multiple sources, one needs to handle uncertainty about the possible orderings. Examples of such “order-incomplete” data include integrated event sequences such as log entries; lists of properties (e.g., hotels and restaurants) ranked by an unknown function reflecting relevance or customer ratings; and documents edited concurrently with an uncertain order on edits. This paper introduces a query language for order-incomplete data, based on the positive relational algebra with order-aware accumulation. We use partial orders to represent order-incomplete data, and study possible and certain answers for queries in this context. We show that these problems are respectively NP-complete and coNP-complete, but identify many tractable cases depending on the query operators or input partial orders. (10.4230/LIPIcs.TIME.2017.4)
  DOI : 10.4230/LIPIcs.TIME.2017.4
• Amplitude and Phase Dereverberation of Harmonic Signals
  
  • Belhomme Arthur
  • Badeau Roland
  • Grenier Yves
  • Humbert Eric
  , 2017. While most dereverberation methods focus on how to estimate the magnitude of an anechoic signal in the time-frequency domain, we propose a method which also takes the phase into account. By ap- plying a harmonic model to the anechoic signal, we derive a formulation to compute the amplitude and phase of each harmonic. These parameters are then estimated by our method in presence of reverberation. As we jointly estimate the amplitude and phase of the clean signal, we achieve a very strong dereverberation, resulting in a significant improvement of standard dereverberation objective measures over the state-of-the-art.
• Lévy NMF for Robust Nonnegative Source Separation
  
  • Magron Paul
  • Badeau Roland
  • Liutkus Antoine
  , 2017. Source separation, which consists in decomposing data into meaningful structured components, is an active research topic in music signal processing. In this paper, we introduce the Positive α-stable (PαS) distributions to model the latent sources, which are a sub- class of the stable distributions family. They notably permit us to model random variables that are both nonnegative and impulsive. Considering the Lévy distribution, the only PαS distribution whose density is tractable, we propose a mixture model called Lévy Non- negative Matrix Factorization (Lévy NMF). This model accounts for low-rank structures in nonnegative data that possibly has high variability or is corrupted by very adverse noise. The model parameters are estimated in a maximum-likelihood sense. We also derive an estimator of the sources, which extends the validity of the Wiener filtering to the PαS case. Experiments on synthetic data and realistic music signals show that Lévy NMF compares favorably with state-of-the art techniques in terms of robustness to impulsive noise and highlight its potential for decomposing nonnegative data.
• Separating Time-Frequency Sources from Time-Domain Convolutive Mixtures Using Non-negative Matrix Factorization
  
  • Leglaive Simon
  • Badeau Roland
  • Richard Gael
  , 2017. This paper addresses the problem of under-determined audio source separation in multichannel reverberant mixtures. We target a semi- blind scenario assuming that the mixing filters are known. Source separation is performed from the time-domain mixture signals in order to accurately model the convolutive mixing process. The source signals are however modeled as latent variables in a time-frequency domain. In a previous paper we proposed to use the modified discrete cosine transform. The present paper generalizes the method to the use of the odd-frequency short-time Fourier transform. In this domain, the source coefficients are modeled as centered complex Gaussian random variables whose variances are structured by means of a non-negative matrix factorization model. The inference procedure relies on a variational expectation-maximization algorithm. In the experiments we discuss the choice of the source representation and we show that the proposed approach outperforms two methods from the literature.
• Explaining the Parameterized Wiener Filter with Alpha-Stable Processes
  
  • Fontaine Mathieu
  • Liutkus Antoine
  • Girin Laurent
  • Badeau Roland
  , 2017. This paper introduces a new method for single-channel denoising that sheds new light on classical early developments on this topic that occurred in the 70’s and 80’s with Wiener filtering and spectral subtraction. Operating both in the short-time Fourier transform domain, these methods consist in estimating the power spectral density (PSD) of the noise without speech. Then, the clean speech signal is obtained by manipulating the corrupted time-frequency bins thanks to these noise PSD estimates. Theoretically grounded when using power spectra, these methods were subsequently generalized to magnitude spectra, or shown to yield better performance by weighting the PSDs in the so-called parameterized Wiener filter. Both these strategies were long considered ad-hoc. To the best of our knowledge, while we recently proposed an interpretation of magnitude processing, there is still no theoretical result that would justify the better performance of parameterized Wiener filters. Here, we show how the α-stable probabilistic model for waveforms naturally leads to these weighted filters and we provide a grounded and fast algorithm to enhance corrupted audio that compares favorably with classical denoising methods.
• Modeling the energy consumption of programs: thermal aspects and Energy/Frequency Convexity Rule
  
  • de Vogeleer Karel
  • Rao Vaddina Kameswar
  • Brandner Florian
  • Jouvelot Pierre
  • Memmi Gérard
  , 2017, pp.1-10. This article summarizes our current studies aiming at a better understanding of the energy consumption of a microprocessor during the execution of an application through a combination of theoretical results and experimental validations, The analysis of the transient thermal behavior and energy gains (ranging from 20 to 40% in some cases) via the adaptation of the clock frequency are of obvious practical interest. A general Passive Cooling Rule (PCR) for an isothermal object subjected to radiation, convection and internal heat generation is proposed. This power-temperature model is observed on an Exynos 5410 processor. Several approximations to this cooling rule are formulated for practical use, particularly online. They are accompanied by general rules for assessing when passive cooling becomes non-negligible compared to active cooling in embedded systems. On another hand, a theoretical framework for the existence of an Energy/Frequency Convexity Rule (EFCR) of program consumption is established. It is validated both by the state of the art and by experimental measurements where the impacts of variation of multiple parameters are studied. Power requirement models are then explained for the Exynos 5410 integrating the clock frequency, temperature and number of active cores. The novelty of these models is that they take into account certain characteristics of the running programs and that they can be directly reused in any simulation for other processors of similar architecture.
• Strengthening fonctional validation of critical system by using Model Checking : application to Instrumentation and control systems in nuclear power plants
  
  • Sun Yanjun
  , 2017. The verification and validation of safety-critical real-time system are subject to stringent standards and certifications. Recent progress in model-based system engineering should be applied to such systems since it allows early detection of defects and formal verification techniques. This thesis proposes a model-based testing (MBT) methodology dedicated to functional validation of safety-critical real-time systems. The method is directed by the structural coverage of the Lustre model co-simulated with tje physical process and also by the functional requirements. It relies on a repetitive use of a model checker to generate coverage-based open-loop test sequences. We also propose a refinement technique of progressively adding environment constraints during test generation. The refinement is expected to support the passage from coverage-based open-loop test sequence to functional requirements-based closed-loop test case. Our methodology also considers the state explosion problem of a model checker and proposes a heuristic called hybrid verification combining model checking and simulation.
• Binary Subchannel Decomposition of Lattice-based Multiple Access Schemes
  
  • Ben Hadj Fredj Abir
  • Belfiore Jean-Claude
  , 2017. Lattice codes used under the Compute-and-Forward paradigm suggest an alternative strategy for the standard Gaussian multiple-access channel (MAC). It has been proven that decoding an integer linear combination of the transmitted codewords enables higher data rates compared to decoding the messages individually. Recent work of Gasptar et al. proposed a new multiple access channel technique that they called Compute-and-Forward Multiple Access Channel (CFMA). The authors proved that, in the case of a two-user MAC and without time sharing, the entire capacity region is achieved using CFMA and a single-user decoder for signal to noise ratios above 1 + √ 2. Throughout this paper, we will work within the Compute-and-Forward framework. The strategy relies on lattice codes, here we will construct lattices using a multi-level coding based construction called construction D. To decode the lattice points, a multi-stage decoder (MSD) should be implemented at the receiver part. In this paper, we propose a new decoding strategy that helps to perform the standard MSD algorithm in a less complex way. The new technique is called Binary Subchannel Decomposition (BSCD). Since, we make use of MSD, we need at each level of the decoder to compute soft-inputs: Log-Likelihood ratios. However the calculations are very complex since we must compute infinite sums of exponentials at each stage. Hereinafter we give efficient LLR approximation for multi-stage decoders. Simulation results about the performance of BSCD are included and compared to the performance of the standard multi-stage decoder.
• A study of the impact of merging schemes on cluster stability in VANETs
  
  • Ren Mengying
  • Zhang Jun
  • Khoukhi Lyes
  • Labiod Houda
  • Vèque Véronique
  , 2017. (10.1109/PIMRC.2017.8292558)
  DOI : 10.1109/PIMRC.2017.8292558
• Cognitive Management of Self -Organized Radio Networks Based on Multi Armed Bandit
  
  • Daher Tony
  • Jemaa Sana Ben
  • Decreusefond Laurent
  , 2017. —Many tasks in current mobile networks are automated through Self-Organizing Networks (SON) functions. The actual implementation consists in a network with several SON functions deployed and operating independently. A Policy Based SON Manager (PBSM) has been introduced to configure these functions in a manner that makes the overall network fulfill the operator objectives. Given the large number of possible configurations (for each SON function instance in the network), we propose to empower the PBSM with learning capability. This Cognitive PBSM (C-PBSM) learns the most appropriate mapping between SON configurations and operator objectives based on past experience and network feedback. The proposed learning algorithm is a stochastic multi-armed bandit, namely the UCB1. We evaluate the performances of the proposed C-PBSM on an LTE-A simulator. We show that it is able to learn the optimal SON configuration and quickly adapts to objective changes.
• Application of the Curvelet Transform for clutter and noise removal in GPR data
  
  • Terrasse Guillaume
  • Nicolas Jean-Marie
  • Trouvé Emmanuel
  • Drouet Emeline
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2017, 10 (10), pp.4280 - 4294. (10.1109/JSTARS.2017.2717960)
  DOI : 10.1109/JSTARS.2017.2717960
• VICKEY: Mining Conditional Keys on Knowledge Bases
  
  • Symeonidou Danai
  • Galárraga Luis
  • Pernelle Nathalie
  • Saïs Fatiha
  • Suchanek Fabian
  , 2017, 10587, pp.661-677. A conditional key is a key constraint that is valid in only a part of the data. In this paper, we show how such keys can be mined automatically on large knowledge bases (KBs). For this, we combine techniques from key mining with techniques from rule mining. We show that our method can scale to KBs of millions of facts. We also show that the conditional keys we mine can improve the quality of entity linking by up to 47 percentage points.
• Tile-based high resolution VR contents delivery
  
  • Grégory Lucas
  • Raulet Mickael
  • Toullec Eric
  • Le Feuvre J.
  , 2017.
• Sphere Decoder with Dichotomic Search
  
  • Khsiba Mohamed-Achraf
  • Rekaya-Ben Othman Ghaya
  , 2017.
• Massive Online Analytics for the Internet of Things (IoT)
  
  • Bifet Albert
  , 2017. Big Data and the Internet of Things (IoT) have the potential to fundamentally shift the way we interact with our surroundings. The challenge of deriving insights from the Internet of Things (IoT) has been recognized as one of the most exciting and key opportunities for both academia and industry. Advanced analysis of big data streams from sensors and devices is bound to become a key area of data mining research as the number of applications requiring such processing increases. Dealing with the evolution over time of such data streams, i.e., with concepts that drift or change completely, is one of the core issues in stream mining. In this talk, I will present an overview of data stream mining, and I will introduce some popular open source tools for data stream mining.
• Secure and Resilient Scheme for Data Protection in Unattanded Wireless Sensor Networks
  
  • Kapusta Katarzyna
  • Memmi Gérard
  • Noura Hassan
  , 2017.
• Arbitrary-shaped Brillouin microwave-photonic filtering by manipulating directly-modulated pump spectrum
  
  • Wei Wei
  • Yi L. L.
  • Jaouën Yves
  • Hu W.
  Optics Letters, Optical Society of America - OSA Publishing, 2017, 42, pp.4083-4086.
• Analysis of Ageing effects on ARTIX7 XILINX FPGA (article) Author
  
  • Slimani Mariem
  • Benkalaia Karim
  • Naviner Lirida
  Microelectronics Reliabilit Journal, 2017.
• Dual Logic Concepts based on Mathematical Morphology in Stratified Institutions: Applications to Spatial Reasoning
  
  • Aiguier Marc
  • Bloch Isabelle
  , 2017.