DPLE: A Privacy-Enhanced and Straggler-Resilient Distributed Learning Framework for Smart Cloud

Yilei Xue, Jianhua Li, Jun Wu

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

Abstract

Distributed machine learning (DML) encounters issues related to privacy and the presence of straggling nodes in smart cloud systems. Lagrange coded computing offers a partial solution to mitigate these concerns. Nonetheless, the privacy of the system becomes vulnerable when the number of semi-trusted nodes surpasses a specific limit, or when external eavesdroppers are present. To confront this hurdle, we introduce a novel framework for distributed learning called DPLE (Differentially Private Lagrange Encoding). This framework employs Lagrange interpolation polynomials to obscure the original data while introducing redundancy, thus improving privacy safeguards and increasing robustness to straggling nodes. It also incorporates artificial noise into local computation outcomes to protect confidential data from potential exposures. Furthermore, we perform theoretical analyses to identify the necessary variance of this noise to maintain desired privacy levels. Experimental validations confirm the efficacy of DPLE and examine how different settings of system parameters impact the accuracies of the results.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE 9th International Conference on Smart Cloud, SmartCloud 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-12
Number of pages6
ISBN (Electronic)9798350389500
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event9th IEEE International Conference on Smart Cloud, SmartCloud 2024 - New York City, United States
Duration: 2024 May 102024 May 12

Publication series

NameProceedings - 2024 IEEE 9th International Conference on Smart Cloud, SmartCloud 2024

Conference

Conference9th IEEE International Conference on Smart Cloud, SmartCloud 2024
Country/TerritoryUnited States
CityNew York City
Period24/5/1024/5/12

Keywords

  • Distributed machine learning
  • Lagrange interpolation polynomial
  • coded computing
  • differential privacy

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Modelling and Simulation

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