Cyber Security in Chipless Radio Frequency Identification (RFID)

Chipless RFID tags offer a low-cost, lightweight solution for identification but are highly vulnerable to cloning due to their lack of cryptographic capability. Existing fingerprinting methods rely on bulky, expensive equipment and are sensitive to environmental noise. This thesis investigates practical and robust authentication approaches by leveraging compact commercial reader, deep neural networks for clone detection, and image-based fingerprinting techniques resilient to noisy conditions. The outcomes advance physical-layer authentication of chipless RFID tags, providing scalable and effective solutions to enhance their security in real-world applications.