This thesis investigates the roles of Software Defined-Radio and 5G technologies in shaping the future of wireless networks, with a focus on the dual aspects of innovation and security. We illustrate the research challenges and solutions that leverage the observation of the usage and evolution over time of the electromagnetic spectrum on a large scale.The first part of the thesis aims to address privacy issues that arise from the widespread use and flexibility of Software Defined-Radio technology. We show how few low-cost passive sensors can be misused for unwanted surveillance. In our study, we demonstrate that just a few inexpensive Software Defined-Radios dongles can track a person’s movements through car tire pressure sensors, highlighting new security weaknesses that can be present in the protocols of everyday Internet of Things wireless devices.

In the second part, we first investigate the design of solutions for protecting the spectrum that are based on deploying a network of low-cost Software Defined-Radio front-end, and then move to high-end 5G Radio Access Network. First, we propose a novel framework for classifying spectrum signals. Here we still utilize a network of low-cost Software Defined-Radio boards and a centralized backend system for processing data in the frequency domain using artificial intelligence classifiers. The work highlights how scaling up this spectrum monitoring system to cover large areas brings its own challenges, such as increased costs. We then propose that integrating this system within the 5G network, leveraging the emerging Open Radio Access Network architecture could offer an innovative cost-effective alternative solution. Staying within the context of the 5G wireless network, we then introduce Det-RAN, a framework designed to mitigate specific vulnerabilities within the 5G protocol. Det-RAN takes a data-driven method, analyzing spectrum data and applying cross-layer analysis to identify and block security threats in 5G networks, all in real-time and in line with O-RAN standards. Through its comprehensive investigation and proposed solutions, the thesis seeks to encourage discussions about spectrum technology usage, advance the state of the art relative to the research, and tackle new security challenges in wireless networking on a large scale.

About Alessio Scalingi

Alessio Scalingi is a Ph.D. candidate of the Pervasive Wireless Systems Group at IMDEA Networks Institute since January 2020. He worked for six months as PhD intern at the Wireless Networks and Embedded Systems (WiNES) Laboratory in Boston (USA). His current main research interests include Collaborative Spectrum Sensing, Machine Learning, Spectrum Anomaly Detection, Open-RAN, Security in 5G & Beyond Networks. It is at the end of the PhD program in Telecommunication Engineering with the expected thesis defense in June 2024.

PhD Thesis Advisor: Dr. Domenico Giustiniano, IMDEA Networks Institute, Spain

University: University Carlos III of Madrid, Spain

Doctoral Program: Telematic Engineering

PhD Committee members:

• President: Suman Banerjee, Professor, University of Wisconsin-Madison
• Secretary: Joerg Widmer, Research director, IMDEA Networks Institute, Madrid, España
• Panel member: Marina Petrova, Professor, RWTH Aachen University