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Efficient TMVP-Based Polynomial Convolution on GPU for Post-Quantum Cryptography Targeting IoT Applications

 
dc.contributor.authorHafeez, Muhammad Asfand
dc.contributor.authorLee, Wai-Kong
dc.contributor.authorKarmakar, Angshuman
dc.contributor.authorHwang, Seong Oun
dc.date.accessioned2024-09-30T10:23:13Z
dc.date.available2024-07-20T18:12:00Z
dc.date.available2024-09-30T10:23:13Z
dc.date.issued2024
dc.description.wosFundingTextThis work was supported in part by the Gachon University Research Fund under Grant GCU-202304050001; in part by the National Research Foundation of Korea funded by the Ministry of Science and ICT under Grant 2022H1D3A2A02081848; and in part by the Circle Foundation (Republic of Korea) for one year since December 2023 as Quantum Security Research Center selected as the 2023 The Circle Foundation Innovative Science Technology Center under Grant 2023 TCF Innovative Science Project-05.
dc.identifier.doi10.1109/JIOT.2024.3384507
dc.identifier.issn2327-4662
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/44190
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.source.beginpage23428
dc.source.endpage23443
dc.source.issue13
dc.source.journalIEEE INTERNET OF THINGS JOURNAL
dc.source.numberofpages16
dc.source.volume11
dc.subject.keywordsMULTIPLIERS
dc.title

Efficient TMVP-Based Polynomial Convolution on GPU for Post-Quantum Cryptography Targeting IoT Applications

dc.typeJournal article
dspace.entity.typePublication
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