Then, we provide a comparative analysis between the existing definitions and our new notions, by classifying existing PUF implementations with respect to them. In this process, we use several new and unpublished machine learning results. The outcome of this comparative classification is that our definitions seem to match the current PUF landscape well, perhaps better than previous definitions. Finally, we analyze the security and practicality features of Strong and Obfuscating $t$-PUFs in concrete applications, obtaining further justification for the split into two notions.
Category / Keywords: implementation / Physical Unclonable Functions, Foundations of Cryptography, Machine Learning Date: received 10 Jun 2009 Contact author: ruehrmai at in tum de Available format(s): PDF | BibTeX Citation Version: 20090611:124146 (All versions of this report) Discussion forum: Show discussion | Start new discussion