CITI Talk: “Distributed Hypothesis Testing over Multi-User Channels”, Prof. Michele Wigger (Telecom ParisTech), 10am, amphitheater Émilie du Châtelet (Marie Curie Library-INSA de Lyon)

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Abstract

As part of the internet of things (IoT), the number of sensor nodes that wish to communicate with each other has exploded and is expected to further increase dramatically. Such an increase of communication devices inherently leads to involved communication and hypothesis testing scenarios, and thus calls for new coding and testing strategies. The talk presents new strategies and corresponding error exponents for different network scenarios, and it proves information-theoretic optimality of the proposed strategies in some cases. Special attention is given to scenarios where information collected at a sensor is desired at multiple decision centres and where communication is multi-hop involving sensor nodes as relays. In these networks, sensors generally compete for network resources, and relay sensors can process received information with sensed information or forward intermediate decisions to other nodes. Depending on the studied error exponents, some of these intermediate decisions require special protection mechanisms when sent over the network. The talk is based on joint work with Sadaf Salehkalaibar, Roy Timo, and Ligong Wang.


CITI Talk: “Coding for Cloud-RAN Downlink Channels”, Prof. Gerhard Kramer (TU Munchen), 9am, amphitheater Émilie du Châtelet (Marie Curie Library-INSA de Lyon)

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Abstract

The downlink of a cloud radio accessnetwork (C-RAN) architecture can be modeled as a diamond network. The baseband unit (BBU) is connected to remote radio heads (RRHs) via fiber links that are modeled as rate-limited bit pipes. Bounds on the rates for reliable communication are evaluated for single-antenna RRHs. A lower bound is based on Marton’s coding, which facilitates dependence across the RRH signals. An upper bound uses Ozarow’s technique to augment the system with an auxiliary random variable. The bounds are studied over scalar Gaussian C-RANs and are shown to meet and characterize the capacity for interesting regimes of operation. The bounds are also evaluated for an abstract model: a noise-free binary adder channel (BAC). The capacity of the BAC is established for all ranges of bit-pipe capacities, which seems to yield a new combinatorial result on sum sets. This work is based on joint work with Shirin Saeedi Bidokhti and Shlomo Shamai.


CITI Talk: “Statistical Learning via Information Bottleneck”, Prof. Abdellatif Zaidi (Université Paris-Est Marne la Vallée), 4pm, room TD-E

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Abstract

We connect the information flow in a neural network to sufficient statistics; and show how techniques that are rooted in information theory, such as the source-coding based information bottleneck method can lead to improved architectures, as well as a better understanding of the theoretical foundation of neural networks, viewed as a cascade compression network. We illustrate our results and view through some numerical examples.


PhD Defense: “Noisy Channel-Output Feedback in the Interference Channel” by Victor Quintero, 12th of December 2017, at 14h, in the amphitheater Émilie du Châtelet – Marie Curie Library – INSA de Lyon

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Jury

  • Prof. Michèle WIGGER, Reviewer, Télécom Paristech, France.
  • Prof. Abdellatif ZAIDI, Reviewer, Université Paris-Est Marne la Vallée, France.
  • Prof. Inbar FIJALKOW, Examiner, Université de Cergy-Pontoise, France.
  • Prof. H. Vincent POOR, Examiner, Princeton University, USA.
  • Prof. Gerhard KRAMER, Examiner, Technische Universität München, Germany.
  • Prof. David GESBERT, Examiner, Eurecom, France.
  • Prof. Jean-Marie GORCE, Thesis Director, Université de Lyon, France.
  • Dr. Samir M. Perlaza, Thesis Advisor, INRIA, France.
  • Prof. Iñaki Esnaola, Guest, University of Sheffield, UK.

Abstract
In this thesis, the two-user Gaussian interference channel with noisy channel-output feedback (GIC-NOF) is studied from two perspectives: centralized and decentralized networks.

From the perspective of centralized networks, the fundamental limits of the two-user GIC- NOF are characterized by the capacity region. One of the main contributions of this thesis is an approximation to within a constant number of bits of the capacity region of the two-user GIC-NOF. This result is obtained thanks to the analysis of a simpler channel model, i.e., a two-user linear deterministic interference channel with noisy channel-output feedback (LDIC- NOF). The analysis to obtain the capacity region of the two-user LDIC-NOF provides the main insights required to analyze the two-user GIC-NOF.

From the perspective of decentralized networks, the fundamental limits of the two-user decentralized GIC-NOF (D-GIC-NOF) are characterized by the η-Nash equilibrium (η-NE) region. Another contribution of this thesis is an approximation to the η-NE region of the two-user GIC-NOF, with η > 1. As in the centralized case, the two-user decentralized LDIC-NOF (D-LDIC-NOF) is studied first and the lessons learnt are applied in the two-user D-GIC-NOF. The final contribution of this thesis consists of a closed-form answer to the question: “When does channel-output feedback enlarge the capacity or η-NE regions of the two-user GIC-NOF or two-user D-GIC-NOF?”. This answer is of the form: Implementing channel-output feedback in transmitter-receiver i enlarges the capacity or η-NE regions if the feedback SNR is beyond SNRi*, with i∈{1,2}. The approximate value of SNRi* is shown to be a function of all the other parameters of the two-user GIC-NOF or two-user D-GIC-NOF.


CITI Talk: “Body Impedance for Authentication, Key Generation and Device Pairing”, Kasper Rasmussen, Associate Professor (University of Oxford), December 8th 10:30, RobIoT room

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Abstract

Body Impedance is an effective biometric because each human body
exhibits a unique response to a signal applied at the palm of one hand
and measured in the palm of the other hand. We will see how body
impedance can be used both as a traditional biometric; to generate
cryptographic keys for use in traditional security purposes; or for
device pairing.

Our device pairing scheme is based on the idea that two devices can
pair, if they are physically held by the same person (at the same
time). To pair two devices, a person touches a conductive surface on
each device. While the person is in contact with both devices, the
human body acts as a transmission medium for intra-body communication
and the two devices can communicate through the body. This body
channel is used as part of a pairing protocol which allows the devices
to agree on a mutual secret and, at the same time, extract physical
features to verify that they are being held by the same person. We
prove that our device pairing protocol is secure with respect to a
strong threat model and we build a proof of concept set-up and conduct
experiments with 15 people to verify the idea in practice

Bio

Kasper Rasmussen is an Associate Professor in the Computer Science
Department at the University of Oxford. He joined the department in
2013 and in 2015 was awarded a University Research Fellowship from the
Royal Society in London. Prior to being at Oxford, Kasper Rasmussen
spent two years as a post-doc at University of California, Irvine.
Kasper Rasmussen did his Ph.D. with prof. Srdjan Capkun at the
Department of Computer Science at ETH Zurich (Switzerland), where he
worked on security issues relating to secure time synchronization and
secure localization with a particular focus on distance bounding. His
thesis won the “ETH Medal” for an outstanding dissertation from the
Swiss Federal Institute of Technology and he was additionally awarded
the Swiss National Science Foundation (SNSF), Fellowship for
prospective researchers.


PhD Defense: “Wi-Fi Tracking: Fingerprinting Attacks and Counter-Measures” by Célestin Matte, December 7th at 1:30pm in Amphi Chappe

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Jury

Reviewers :
Nguyen, Benjamin, Professeur des universités, INSA Centre Val de Loire
Rasmussen, Kasper, Associate professor, University of Oxford

Members:
Chrisment, Isabelle, Professeur des universités, Université de Lorraine
Risset, Tanguy, Professeur des universités, INSA Lyon
Neumann, Christoph, Principal scientist, Technicolor

Supervisors :
Minier, Marine, Professeur des universités, Université de Lorraine
Cunche, Mathieu, Maître de conférences, Insa Lyon

Abstract

Wi-Fi Tracking: Fingerprinting Attacks and Counter-Measures

The recent spread of everyday-carried Wi-Fi-enabled devices (smartphones, tablets and wearable devices) comes with a privacy threat to their owner, and to society as a whole. These devices continuously emit signals which can be captured by a passive attacker using cheap hardware and basic knowledge. These signals contain a unique identifier,
called the MAC address. To mitigate the threat, device vendors are currently deploying a countermeasure on new devices: MAC address randomization. Unfortunately, we show that this mitigation, in its current state, is insufficient to prevent tracking.

To do so, we introduce several attacks, based on the content and the timing of emitted signals. In complement, we study implementations of MAC address randomization in some recent devices, and find a number of shortcomings limiting the efficiency of these implementations at preventing device tracking.

At the same time, we perform two real-world studies. The first one considers the development of actors exploiting this issue to install Wi-Fi tracking systems. We list some real-world installations and discuss their various aspects, including regulation, privacy implications, consent and public acceptance. The second one deals with the spread of MAC address randomization in the devices population.

Finally, we present two tools: an experimental Wi-Fi tracking system for testing and public awareness raising purpose, and a tool estimating the uniqueness of a device based on the content of its emitted signals even if the identier is randomized.