A Novel Key Generation Method for Group-Based Physically Unclonable Function Designs

In recent years, physically unclonable functions (PUFs) have gained significant attraction in IoT security applications, such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of different devices to generate unique fingerprints for applications. When generating PUF-based secret keys, reliability entropy keys are vital factors. This study proposes a novel method from set measurements. Firstly, it formulates group-based problem an optimization solves using integer linear programming (ILP), which guarantees finding optimum solution. Then, scheme extraction groups is proposed, we call positioning syndrome coding (PSC). The use ILP well introduction PSC facilitates high-entropy with low error correction costs. These new methods been tested by applying them on output capacitor network PUF. results confirm application high-quality keys.