A Fuzzy Logic-Based System for Detecting Trustable Physical Unclonable Functions

Physical Unclonable Functions (PUFs) provide a promising security mechanism by leveraging inherent process variations to generate unique, hardware-bound secrets without requiring secure storage. However, ensuring PUF reliability and detecting potential tampering remain critical challenges. This paper presents a fuzzy logic-based classification system that determines the authenticity of PUF responses using three key metrics: Reliability, Stability, and Reliability Invariance. The system classifies PUF responses into three categories: Trustable, Tampered, and Undecided. This approach enhances the automatic detection of unreliable responses that may indicate tampering while ensuring the fidelity of PUF responses over time. By applying fuzzy inference rules, our method achieves high accuracy in distinguishing between trustworthy and compromised PUFs. Experimental results demonstrate the effectiveness of our approach, making it a valuable method and tool for hardware security applications.