A Fast Deep Learning Method for Security Vulnerability Study of XOR PUFs
A Fast Deep Learning Method for Security Vulnerability Study of XOR PUFs
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Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Contents
Physical unclonable functions (PUF) are emerging as a promising alternative to traditional cryptographic protocols for IoT authentication. XOR Arbiter PUFs (XPUFs), a group of well-studied PUFs, are found to be secure against machine learning (ML) attacks if the XOR gate is large enough, as both the number of CRPs and the computational time require...
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Full title
A Fast Deep Learning Method for Security Vulnerability Study of XOR PUFs
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TN_cdi_proquest_journals_2548420328
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2548420328
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ISSN
2079-9292
E-ISSN
2079-9292
DOI
10.3390/electronics9101715
