Abstract

Physical unclonable functions (PUFs) are hardware security primitives that offer a lightweight security solution for constrained devices in the Internet of Things. The challenges facing PUFs security scaling have so far hindered their wide-scale deployment beyond simple key generation primitives. Although physically unclonable, PUFs are vulnerable to soft modeling attacks. Many PUF security enhancements impose significant implementation overhead, which could be problematic for devices operating in a constrained environment. This work introduces the Cross-Feed (XFeed) PUF, a highly efficient PUF circuit resilient against machine learning attacks while requiring a small circuit implementation area. In the XFeed PUF, arbiters feed intermediate race conditions to adjacent PUF rows to increase the non-linearity of the PUF system. A systematic categorization and benchmarking of the possible interconnection strategies are performed to determine the near-optimal connection schemes for the introduced XFeed PUF. The results showed that the XFeed PUF has superior security efficiency and scalability compared to other arbiter PUF-based enhancements.

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