Dissertation: Study helps strengthen the security of drone-assisted wireless communication
The new era of 5G and the upcoming 6G brings incredible opportunities, but also significant challenges in securing information. With the rise of information exchanges in wireless networks, protecting sensitive data from potential eavesdroppers is more critical than ever.
Xinying Kilpi-’s dissertation explores solutions for enhancing transmission security in unmanned aerial vehicle (UAV) assisted wireless networks. UAV’s, commonly referred to as drones, can be used to strengthen wireless network signals in situations like data collection or temporary network construction.
In her study Kilpi-Chen is using advanced PLS and covert communication techniques to guarantee security. PLS, often referred to as a security technique at the physical layer by using the randomness of wireless channel links, can be used to enhance communication confidentiality. The PLS is first integrated with covert communication for the first time to significantly enhance the security performance.
“UAVs are increasingly used for data collection and delivery in various fields, but their wireless networks are vulnerable to eavesdropping. For example, when a drone delivers packages to a customer, the customer's personal information could be stolen by unauthorized parties through wireless links. My work provides practical solutions to ensure secure communication in these scenarios,” Kilpi-Chen explains.
Kilpi-’s research is the first to explore and combine covert communication and PLS techniques, creating a dual-layered defense mechanism for secure transmissions. While covert communication focuses on hiding the very existence of transmissions to avoid detection, PLS provides mathematical guarantees of secrecy even when the transmission is detected.
“By merging these two paradigms, we can achieve previously unattainable level of communication security. Different from conventional covert communications, this method also prevents eavesdroppers from decoding even when covert communication failed and being detected,” Kilpi-Chen says.
In her study Kilpi-Chen proposes a new UAV transmission framework to prevent eavesdropping by optimizing transmit power and blocklength, reducing signals received by eavesdroppers. She also designs drone trajectories, duration, and scheduling to enhance energy efficiency.
“Another highlight of my work is an intelligent reflecting surface (IRS) that can be used on UAV network. IRS method redirects wireless signals and utilizes jamming signals to protect confidential signals from eavesdropping while maintaining high communication quality,” Kilpi-Chen tells.
According to Kilpi-Chen her work can be applied in industries where secure and efficient UAV communications are critical, such as logistics or telecommunications and make the UAV communications safer.
Xinying Kilpi-Chen defends her doctoral dissertation “Secure Transmission Strategies in UAV-Assisted Wireless Networks”. Opponent is Associate Professor Hirley Alves (University of Oulu) and custos is Associate Professor Ilkka Pölönen (Ģֱ).
The language of the dissertation is English.
The dissertation can be followed in the lecture hall Agora Auditorium 3 (Ag B103) or online.
Link to the online event:
