Complementary IBS: Application specific error correction for PUFs

Abstract

In this contribution, we present Complementary Index-Based Syndrome coding (C-IBS), a new and flexible fuzzy embedder for Physical Unclonable Functions (PUFs). C-IBS applies IBS several times to the same group of PUF outputs. The additional parameter permits an application specific tradeoff between error correction capability and implementation complexity. We demonstrate the flexibility of C-IBS by providing efficient solutions that optimize error correction, helper data size or decoder complexity for a well-known key generation scenario. Further, we present encoding criteria that characterize C-IBS fuzzy embedders in general. A hardware implementation is compared to previous work and substantiates the efficiency of C-IBS. The low implementation complexity of C-IBS facilitates the usage for resource constrained cryptographic applications.