Evaluating Dynamic Wavelet Fingerprinting of Chipless RFID Tags in Detecting Counterfeits in Noiseless and Noisy Environments

Radio Frequency Identification (RFID) plays a crucial role in object identification in the rapidly changing world of the Internet of Things (IoT). Therefore, innovating a simple and adaptive solution to evaluate tag authenticity to combat counterfeit products is increasingly important. This study introduces a novel approach using the Dynamic Wavelet Fingerprint (DWFP) technique to produce fingerprint-like images for chipless RFID tags. These fingerprints are created by using tag's distinct electromagnetic (EM) response, which is produced through natural randomness added to the planar resonator configuration in the fabrication process. The unique fingerprints provide a simple and intuitive way to identify cloned tags. The research rigorously assesses the efficacy of these fingerprints in detecting cloned tags across noiseless and noisy environment. After analyzing twelve different mother wavelets and utilizing two slicing algorithms, this study presents optimal combinations that exhibit an increased diversity among cloned tags and resilience against noise. The findings highlight the DWFP technique as a robust solution for bolstering RFID tag security. This research offers new possibilities in image-based identification, demonstrating the potential of DWFP to transform the authentication of RFID tags and mitigate counterfeiting risks.