Enhancing the Resiliency of Multi-bit Parallel Arbiter-PUF and Its Derivatives Against Power Attacks

Embedded systems utilize Physically Unclonable Functions (PUFs) for authentication and identification purposes. However, modeling PUFs’ behavior via machine-learning methods has received utmost attention. Current research on modeling PUFs mainly targets a single PUF instance (PUF producing a single-bit response per query). It is admittedly more challenging to attack multi-bit parallel PUFs (with \(M>1\) PUF instances). In this work, we first target a multi-bit (mainly \(M=2\)-bit) parallel arbiter-PUF using its power traces, then introduce a hybrid countermeasure, combining Dual Rail Logic and Randomized Initialization Logic mechanisms, to thwart such attack. In addition, we explore Randomized Arbiter Swapping and Randomized Response Masking mitigation techniques for providing further protection for parallel PUFs against modeling attacks. To mimic the PUFs’ behavior in real silicon, we add noise artificially in our simulations. The results confirm the high success of the launched attack for the unprotected-PUF, and the resiliency of our countermeasures.