Annonce

Les commentaires sont clos.

Ph.D. position in information science at L2S, CentraleSupelec - Structured Approches to Physical Layer Security and Sensing

12 Février 2023

Catégorie : Doctorant

Open Ph.D. position on the theoretical foundations of information science
Structured Approaches to Physical Layer Security and Sensing

Ph.D. opportunity in the Laboratory of Signals and Systems (L2S), CentraleSupélec, Université Paris-Saclay

Keywords

  • Information theory
  • Machine learning
  • Estimation and detection
  • Wireless communications

Research scope

The recent paradigms in telecommunication and networks assume a myriad of interconnected agents (Internet of Things, MU-MIMO) of some transmitting personal and sensitive data. This raises new information security concerns, notably the risk of eavesdropping on the transmitted signal or the leakage of physical information on the user, such as its localization. While the privacy of communication is often handled over the transport layer by cryptographic means, the current surge of interest in physical layer security, which aims to leverage the structural properties of a communication channel to generate privacy, has opened numerous possibilities to strengthen user security. Unlike classical cryptography, physical layer security encodes the information in the form of a problem that is statistically hard for unauthorized parties by harnessing specific hypotheses on the transmission channel.Physical layer security offers complementary guarantees to usual cryptography, such as the possibility of concealing a communication, and is robust to flaws in the software implementation of ciphers.

The general research scope of the Ph.D. project is at the intersection of Information Theory, Signal Processing, and Wireless Communication. It will investigate the statistical aspects of estimation and detection tasks occurring on the physical layer of wireless telecommunication networks and propose coding schemes to harden/ease the sensing of targets and secure transmission in wireless networks. Connex research areas include but are not limited to:

- Communication and sensing: The problem of probing and transmitting information in a wireless environment at the same time.

- Machine learning-aided wireless estimation: Developing neural network-based estimators to estimate channels and targets in a data-driven radio environment.

-Covert communication: An information-theoretic framework to conceal a transmission in the ambient noise.

 

During the Ph.D. project, the successful applicant will be strongly encouraged to develop and strengthen his/her own research interests and to construct his/her personal research plan within this generic scope.

Possibility to start the Ph.D. project with an internship on spring/summer 2023. More information on the Ph.D. subject and on the application process are available at https://maximeferreira.github.io/