Photos: © Michael Schwettmann
Wireless connectivity drives digital innovation and is becoming increasingly ubiquitous. However, a downside of this trend is the burgeoning of new types of privacy concerns:
The radio wave propagation underlying the wireless communication gives away sensitive information to adversaries – regardless of cryptographic measures. Such types of attacks are known as adversarial wireless sensing. For example, adversaries can launch remote surveillance attacks by simply observing the wireless traffic of Wi-Fi devices. Previous work has already demonstrated practical motion detection attacks based on employing physical layer channel information. In this work, we seek to investigate the potential of Intelligent Reflecting Surfaces (IRS) to aid such
attacks. The IRS is a new type of wireless infrastructure, essentially a digitally configurable reflector towards radio waves. In your thesis, you will first conduct practical wireless reconnaissance attacks and then try to improve them by utilizing an IRS.
This thesis is a follow-up to our previous work IRShield  which we presented at the IEEE Symposium on Security and Privacy (S&P) in 2022. We are looking for a highly motivated candidate, ideally with experience in Python and C programming and with basic knowledge of wireless systems or signal processing. The thesis will have strong focus on practical aspects, including real-world implementation and experimentation. As part of the thesis, there is potential for a joint scientific publication. The thesis is offered in cooperation by the Max Planck Institute for Security and Privacy (MPI-SP) and the RUB chairs Digital Communication Systems (DKS) and Systems Security (SysSec). https://doi.ieeecomputersociety.org/10.1109/SP46214.2022.9833676
- Knowledge of Python and C
- Basic knowledge of wireless systems or signal processing