Publications

2018

• Combining quantum and computational approaches to upgrade secure networks
  
  • Alleaume Romain
  , 2018.
• Simulation of 2 μm thulium-doped single clad silica fiber amplifiers by characterization of the 3F4-3H6 transition
  
  • Romano Clément
  • Tench Robert
  • Delavaux Jean-Marc
  Optics Express, Optical Society of America - OSA Publishing, 2018.
• Influence of the upper nonlasing state on the route to chaos of InAs/GaAs quantum dot lasers
  
  • Huang Heming
  • Arsenijevi Dejan
  • Bimberg Dieter
  • Grillot Frédéric
  , 2018.
• 10-Gb/s Floor-Free Transmission of a Hybrid III-V on Silicon Distributed Feedback Laser with Optical Feedback
  
  • Gomez Sandra
  • Huang Heming
  • Grillot Frédéric
  , 2018.
• Output Fisher embedding regression
  
  • Djerrab Moussab
  • Garcia Alexandre
  • Sangnier Maxime
  • d'Alché-Buc Florence
  Machine Learning, Springer Verlag, 2018, 107 (8-10), pp.1229-1256. (10.1007/s10994-018-5698-0)
  DOI : 10.1007/s10994-018-5698-0
• Speed Index: Relating the Industrial Standard for User Perceived Web Performance to web QoE
  
  • Hossfeld Tobias
  • Metzger Florian
  • Rossi Dario
  , 2018.
• Broadband High Gain Polarization-Maintaining Holmium-doped Fiber Amplifiers
  
  • Tench Robert
  • Romano Clément
  • Delavaux Jean-Marc
  , 2018, pp.paper Mo3E.3.
• Dual Polarization nonlinear frequency division multiplexing transmission
  
  • Gemechu Wasyhun A.
  • Gui Tao
  • Song Mengdi
  • Wabnitz Stephano
  • Hafermann Hartmut
  • Tao Lau Alan Pak
  • Yousefi Mansoor
  • Jaouën Yves
  IEEE Photonics Technology Letters, Institute of Electrical and Electronics Engineers, 2018, 30 (18), pp.1589-1592.
• Automatic Detection of Depressive States from Speech
  
  • Mendiratta Aditi
  • Scibelli Filomena
  • Esposito Antonietta
  • Capuano Vincenzo
  • Likforman-Sulem Laurence
  • Maldonato Mauro
  • Vinciarelli Alessandro
  • Esposito Anna
  Entropy, MDPI, 2018, 69 (6), pp.301-314. This paper proposes a speech-based method for automatic depression classification. The system is based on ensemble learning for Convolutional Neural Networks (CNNs) and is evaluated using the data and the experimental protocol provided in the Depression Classification Sub-Challenge (DCC) at the 2016 Audio–Visual Emotion Challenge (AVEC-2016). In the pre-processing phase, speech files are represented as a sequence of log-spectrograms and randomly sampled to balance positive and negative samples. For the classification task itself, first, a more suitable architecture for this task, based on One-Dimensional Convolutional Neural Networks, is built. Secondly, several of these CNN-based models are trained with different initializations and then the corresponding individual predictions are fused by using an Ensemble Averaging algorithm and combined per speaker to get an appropriate final decision. The proposed ensemble system achieves satisfactory results on the DCC at the AVEC-2016 in comparison with a reference system based on Support Vector Machines and hand-crafted features, with a CNN+LSTM-based system called DepAudionet, and with the case of a single CNN-based classifier. (10.1007/978-3-319-56904-8_29)
  DOI : 10.1007/978-3-319-56904-8_29
• CCFI-Cache: A Transparent and Flexible Hardware Protection for Code and Control-Flow Integrity
  
  • Danger Jean-Luc
  • Facon Adrien
  • Guilley Sylvain
  • Heydemann Karine
  • Kühne Ulrich
  • Si Merabet Abdelmalek
  • Timbert Michaël
  , 2018, pp.529-536. In this paper we present a hardware based solution to verify simultaneously Code and Control-Flow Integrity (CCFI), aiming at protecting microcontrollers against both cyber-and physical attacks. This solution is non-intrusive as it does not require any modification of the CPU core. It relies on two additional hardware blocks external to the CPU: The first one – called CCFI-cache – acts as a dedicated cache for the storage of information to check the code and control-flow integrity, and the second one – CCFI-checker – performs control-flow and code integrity verification. Based on a RISC-V platform implementation, we show that the proposed scheme is able to perform online CCFI validation at the price of a small hardware area overhead and doubling the size of the. text section. In most cases, the impact on the run-time performance is on average 32 percent, offering for the first time a generic and practical hardware-enabled cyber-security solution. (10.1109/DSD.2018.00093)
  DOI : 10.1109/DSD.2018.00093
• OpenSSL Bellcore's Protection Helps Fault Attack
  
  • Carre Sebastien
  • Desjardins Matthieu
  • Facon Adrien
  • Guilley Sylvain
  , 2018, pp.500-507. Faults in software implementations target both data and instructions at different locations. Bellcore attack is a well-known fault attack that is able to break CRT-RSA. In response, cryptographic libraries such as OpenSSL are designed with protections. In this paper, we show two new fault locations on OpenSSL implementation of the CRT-RSA signature that restore the Bellcore attack and break OpenSSL protection against it. Quite surprisingly, one of the fault we found is made possible because of the existence of such protection. (10.1109/DSD.2018.00089)
  DOI : 10.1109/DSD.2018.00089
• Qu'est-ce qu'une belle photo ? Essai sur l'esthétique en photographie numérique
  
  • Maître Henri
  , 2018.
• Analysis of Mixed PUF-TRNG Circuit Based on SR-Latches in FD-SOI Technology
  
  • Danger Jean-Luc
  • Yashiro Risa
  • Graba Tarik
  • Mathieu Yves
  • Si-Merabet Abdelmalek
  • Sakiyama Kazuo
  • Miura Noriyuki
  • Nagata Makoto
  , 2018, pp.508-515.
• Video Quality Evaluation for Tile-Based Spatial Adaptation
  
  • Yousef Hiba
  • Le Feuvre J.
  • Valenzise Giuseppe
  • Hulusic Vedad
  , 2018, pp.1-6. The following topics are dealt with: learning (artificial intelligence); feature extraction; video coding; object detection; data compression; image classification; image coding; image representation; image reconstruction; optimisation. (10.1109/MMSP.2018.8547126)
  DOI : 10.1109/MMSP.2018.8547126
• An improved analysis of reliability and entropy for delay PUFs
  
  • Schaub Alexander
  • Danger Jean-Luc
  • Guilley Sylvain
  • Rioul Olivier
  , 2018. (10.1109/DSD.2018.00096)
  DOI : 10.1109/DSD.2018.00096
• ALGeoSPF: A Hierarchical Factorization Model for POI Recommendation
  
  • Griesner Jean-Benoît
  • Abdessalem Talel
  • Naacke Hubert
  • Dosne Pierre
  , 2018, pp.87-90. (10.1109/ASONAM.2018.8508249)
  DOI : 10.1109/ASONAM.2018.8508249
• DoF in Sectored Cellular Systems with BS Cooperation Under a Complexity Constraint
  
  • Gelincik Samet
  • Wigger Michèle
  • Wang Ligong
  , 2018. The paper presents upper and lower bounds on the per-user degrees of freedom (DoF) of a sectored hexagonal cellular model where neighboring basestations (BS) can cooperate during at most κ interaction rounds over backhaul links of capacities μ = μ DoF ·[1/2]log P, with P denoting the transmit power at each mobile user. The lower bound is based on practically implementable beamforming and adapts the way BSs cooperate to the sector structure of the cells. It improves over the naive approach that ignores this sector structure. The upper bound is information-theoretic and holds for all possible coding schemes, including for example ergodic interference alignment whose practical implementation currently seems out of reach. Lower and upper bounds show that the complexity constraint imposed by limiting the number of interaction rounds κ indeed limits the largest achievable DoF. In particular, irrespective of the backhaul capacity μ, the per-user DoF cannot exceed a threshold which depends on κ. (10.1109/ISWCS.2018.8491081)
  DOI : 10.1109/ISWCS.2018.8491081
• Throughput-efficient Relay assisted Hybrid ARQ
  
  • Khreis Alaa
  • Ciblat Philippe
  • Bassi Francesca
  • Duhamel Pierre
  , 2018. Reliable data transmission within wireless communication systems can be obtained via various means, including (i) Hybrid Automatic Repeat reQuest (HARQ) mechanisms which allow retransmission of incorrectly decoded packets; (ii) Additional nodes, called relays, which may also help the transmission by retransmitting these packets. An efficient combination of both techniques is therefore of great interest. This paper investigates a relay assisted HARQ protocol aiming at maximizing the system throughput. The protocol allows the source to transmit a new message during the same time-slot in which the relay is retransmitting a previous message. By using an efficient interference canceler at the destination, the numerical results show significant throughput gain compared to standard approaches. (10.1109/iswcs.2018.8491051)
  DOI : 10.1109/iswcs.2018.8491051
• A Storage-Computation-Communication Tradeoff for Distributed Computing
  
  • Yan Qifa
  • Yang Sheng
  • Wigger Michèle
  , 2018, pp.1-5. This paper investigates distributed computing systems where computations are split into “Map” and “Reduce” functions. A new coded scheme, called distributed computing and coded communication (D3C), is proposed, and its communication load is analyzed as a function of the available storage space and the number of intermediate values (IVA) to be computed. D3C achieves the smallest possible communication load for a given storage space, while a smaller number of IVAs need to be computed compared to Li et al.'s coded distributed computing (CDC) scheme. More generally, our scheme can flexibly trade between storage space and the number of IVAs to be computed. Communication load is then analyzed for any given tradeoff. (10.1109/iswcs.2018.8491052)
  DOI : 10.1109/iswcs.2018.8491052
• Quality Assessment of Deep-Learning-Based Image Compression
  
  • Valenzise Giuseppe
  • Purica Andrei
  • Hulusic Vedad
  • Cagnazzo Marco
  , 2018. —Image compression standards rely on predictive coding , transform coding, quantization and entropy coding, in order to achieve high compression performance. Very recently, deep generative models have been used to optimize or replace some of these operations, with very promising results. However, so far no systematic and independent study of the coding performance of these algorithms has been carried out. In this paper, for the first time, we conduct a subjective evaluation of two recent deep-learning-based image compression algorithms, comparing them to JPEG 2000 and to the recent BPG image codec based on HEVC Intra. We found that compression approaches based on deep auto-encoders can achieve coding performance higher than JPEG 2000, and sometimes as good as BPG. We also show experimentally that the PSNR metric is to be avoided when evaluating the visual quality of deep-learning-based methods, as their artifacts have different characteristics from those of DCT or wavelet-based codecs. In particular, images compressed at low bitrate appear more natural than JPEG 2000 coded pictures, according to a no-reference naturalness measure. Our study indicates that deep generative models are likely to bring huge innovation into the video coding arena in the coming years. (10.1109/mmsp.2018.8547064)
  DOI : 10.1109/mmsp.2018.8547064
• A Repetition Scheme for MBSFN Based Mission-Critical Communications
  
  • Daher Alaa
  • Ali Mohammed Shabbir
  • Coupechoux Marceau
  • Godlewski Philippe
  • Ngouat Pierre
  • Minot Pierre
  , 2018, pp.1-6. (10.1109/VTCFall.2018.8690595)
  DOI : 10.1109/VTCFall.2018.8690595
• A new analytical model for the performance evaluation of the uplink transmission in NB-IoT networks
  
  • Nguyen Tuan Anh
  • Martins Philippe
  • Nguyen van Tam
  • Nguyen T. Mai Trang
  , 2019, pp.1-5. NB-IoT has been defined in 3GPP release 13. It modifies LTE radio access procedures and protocols to fulfill energy consumption, low data rate and latency requirements associated with IoT applications. One of the major issues of NB-IoT deployment is the design of performance evaluation models that make it possible to plan and dimension this new system. This work proposes a new analytical model based on stochastic geometry. It provides a closed form expression of the successful transmission of an NB-IoT system in the uplink for a given sensor spatial intensity. The accuracy of the proposed analytical model is validated by simulation. (10.1109/VTCFall.2018.8690677)
  DOI : 10.1109/VTCFall.2018.8690677
• An empirical investigation of botnet as a service for cyberattacks
  
  • Hammi Badis
  • Zeadally Sherali
  • Khatoun Rida
  Transactions on emerging telecommunications technologies, Wiley-Blackwell, 2018, 30 (3), pp.e3537. (10.1002/ett.3537)
  DOI : 10.1002/ett.3537
• A survey on game-theoretic approaches for intrusion detection and response optimization
  
  • Kiennert Christophe
  • Ziad Ismail
  • Debar Hervé
  • Leneutre Jean
  ACM Computing Surveys, Association for Computing Machinery, 2018, 51 (5), pp.1-31. Intrusion Detection Systems (IDS) are key components for securing critical infrastructures, capable of detecting malicious activities on networks or hosts. However, the efficiency of an IDS depends primarily on both its configuration and its precision. The large amount of network traffic that needs to be analyzed, in addition to the increase in attacks' sophistication, renders the optimization of intrusion detection an important requirement for infrastructure security, and a very active research subject. In the state of the art, a number of approaches have been proposed to improve the efficiency of intrusion detection and response systems. In this article, we review the works relying on decision-making techniques focused on game theory and Markov decision processes to analyze the interactions between the attacker and the defender, and classify them according to the type of the optimization problem they address. While these works provide valuable insights for decision-making, we discuss the limitations of these solutions as a whole, in particular regarding the hypotheses in the models and the validation methods. We also propose future research directions to improve the integration of game-theoretic approaches into IDS optimization techniques (10.1145/3232848)
  DOI : 10.1145/3232848
• A practical method for measuring Web above-the-fold time
  
  • da Hora Diego
  • Rossi D.
  • Christophides Vassilis
  • Teixeira Renata
  , 2018. Page load time (PLT) is still the most common application Quality of Service (QoS) metric to estimate the Quality of Experience (QoE) of Web users. Yet, recent literature abounds with interesting proposals for alternative metrics (e.g., Above The Fold, SpeedIndex and variants) that aim at closely capturing how users perceive the Webpage rendering process. However, these novel metrics are typically computationally expensive, as they require to monitor and post-process videos of the rendering process, and have failed to be widely deployed. In this demo, we show our implementation of an open-source Chrome extension that implements a practical and lightweight method to measure the approximated Above-the-Fold (AATF) time, as well as others Web performance metrics. The idea is, instead of accurately monitoring the rendering output, to track the download time of the last visible object on screen (i.e., "above the fold"). Our plugin also has options to save detailed reports for later analysis, a functionality ideally suited for researchers wanting to gather data from Web experiments.