Latency-Aware Inference on Convolutional Neural Network Over Homomorphic Encryption

Takumi Ishiyama, Takuya Suzuki*, Hayato Yamana

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Homomorphic encryption enables privacy-preserving computation in convolutional neural networks (CNNs), keeping their input and output secret from the server; however, it faces long latency because of large overhead of the encryption scheme. This paper tackles shortening the inference latency on homomorphic encryption-enabled CNNs. Since the highest inference accuracy is not always needed depending on real-world applications, finding best-fit combinations of latency and accuracy is also indispensable. We propose a combination of channel-wise packing and a structured pruning technique besides changing the active functions to shorten the inference latency while allowing accuracy degradation. Our experimental evaluation shows that we successfully tune the latency from 8.1 s to 12.9 s depending on the accuracy of 66.52% to 80.96% on the CIFAR-10 dataset.

Original languageEnglish
Title of host publicationInformation Integration and Web Intelligence - 24th International Conference, iiWAS 2022, Proceedings
EditorsEric Pardede, Pari Delir Haghighi, Ismail Khalil, Gabriele Kotsis
PublisherSpringer Science and Business Media Deutschland GmbH
Pages324-337
Number of pages14
ISBN (Print)9783031210464
DOIs
Publication statusPublished - 2022
Event24th International Conference on Information Integration and Web Intelligence, iiWAS 2022, held in conjunction with the 20th International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2022 - Virtual, Online
Duration: 2022 Nov 282022 Nov 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13635 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th International Conference on Information Integration and Web Intelligence, iiWAS 2022, held in conjunction with the 20th International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2022
CityVirtual, Online
Period22/11/2822/11/30

Keywords

  • Channel pruning
  • Convolutional neural network
  • Homomorphic encryption
  • Privacy-preserving machine learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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