Neural Network Training With Homomorphic Encryption (Record no. 645)

000 -LEADER
fixed length control field 01386nam a2200169 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260901030331.0
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fixed length control field 250101s2020 xx o 000 0 eng d
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kentaro Mihara
245 10 - TITLE STATEMENT
Title Neural Network Training With Homomorphic Encryption
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Name of producer, publisher, distributor, manufacturer arXiv
Date of production, publication, distribution, manufacture, or copyright notice 2020
336 ## - CONTENT TYPE
Content type term text
338 ## - CARRIER TYPE
Carrier type term online resource
520 ## - SUMMARY, ETC.
Summary, etc. We introduce a novel method and implementation architecture to train neural networks which preserves the confidentiality of both the model and the data. Our method relies on homomorphic capability of lattice based encryption scheme. Our procedure is optimized for operations on packed ciphertexts in order to achieve efficient updates of the model parameters. Our method achieves a significant reduction of computations due to our way to perform multiplications and rotations on packed ciphertexts from a feedforward network to a back-propagation network. To verify the accuracy of the training model as well as the implementation feasibility, we tested our method on the Iris data set by using the CKKS scheme with Microsoft SEAL as a back end. Although our test implementation is for simple neural network training, we believe our basic implementation block can help the further applications for mo
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open access — freely available to read.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://arxiv.org/pdf/2012.13552v1">https://arxiv.org/pdf/2012.13552v1</a>
Link text Read the full paper (PDF)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Electronic resource (link)
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Withdrawn status Lost status Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Total checkouts Barcode Date last seen Uniform resource identifier Price effective from Koha item type
      Available online Cybersecurity Yegates University Library Yegates University Library Science and Computing 09/01/2026   YGE000906 09/01/2026 https://arxiv.org/pdf/2012.13552v1 09/01/2026 Research paper — read online