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This article introduces a novel approach to address the security challenges of chipless tag systems in the context of Internet of Things (IoT) applications. The proposed technique focuses on preventing tag cloning by leveraging the inherent natural randomness in the fabrication process. A groundbreaking aspect of this research is the utilization of an affordable and portable Multiple Input Multiple Output (MIMO) antenna system in real-world scenarios to detect counterfeit tags. The study begins by validating the precision of the MIMO system, establishing its effectiveness compared to Vector Network Analyzer (VNA) equipment. Additionally, the clone detection system is thoroughly evaluated for accuracy, and improvements are introduced through various Machine Learning (ML) models. The ML techniques used were able to detect clones with 99.78% accuracy, outperforming VNA equipment. This research represents a significant advancement in chipless tag security for IoT applications, offering a cost-effective and efficient solution to the pressing security issue of tag cloning.
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Khan et al. (2024) studied this question.
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