Physical unclonable functions are promising candidates as security primitives for resource-constrained IoT devices . Arbiter PUFs (APUFs) are a group of delay-based PUFs which are highly lightweight in resource requirements but suffer from high susceptibility to machine learning attacks . The challenge input interface incurs low resource overhead and improves PUFs’ resistance against machine-learning attacks . With the interface, experimental attack study shows that all tested PUFs have substantially improved theirresistance against machinelearning attacks, rendering interfaced APUF variants promising candidates for security critical applications, according to the authors of this article . Back to the page you came from .

Author(s) : Yu Zhuang, Khalid T. Mursi, Li Gaoxiang

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Keywords : attacks - pufs - resource - interface - machine -

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