Cryptology ePrint Archive: Report 2022/165
PAC Learnability of iPUF Variants
Durba Chatterjee and Debdeep Mukhopadhyay and Aritra Hazra
Abstract: Interpose PUF~(iPUF) is a strong PUF construction that was shown to be vulnerable against empirical machine learning as well as PAC learning attacks. In this work, we extend the PAC Learning results of Interpose PUF to prove that the variants of iPUF are also learnable in the PAC model under the Linear Threshold Function representation class.
Category / Keywords: foundations / Physically Unclonable Funcitons, PAC Learning, Boolean Functions
Date: received 13 Feb 2022, last revised 14 Feb 2022
Contact author: durba chatterjee94 at gmail com
Available format(s): PDF | BibTeX Citation
Version: 20220220:200529 (All versions of this report)
Short URL: ia.cr/2022/165
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