A Secure Bandwidth-Efficient Treatment for Dropout-Resistant Time-Series Data Aggregation

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Aggregate statistics derived from time-series data collected by individual users are extremely beneficial in diverse fields, such as e-health applications, IoT-based smart metering networks, and federated learning systems. Since user data are privacy-sensitive in many cases, the untrusted aggregator may only infer the aggregation without breaching individual privacy. To this aim, secure aggregation techniques have been extensively researched over the past years. However, most existing schemes suffer either from high communication overhead when users join and leave, or cannot tolerate node dropouts. In this paper, we propose a dropout-resistant bandwidth-efficient time-series data aggregation. The proposed scheme does not incur any interaction among users, involving a solo round of user→aggregator communication exclusively. Additionally, it does not trigger a re-generation of private keys when users join and leave. Moreover, the aggregator is able to output the aggregate value by employing the re-encrypt capability acquired during a one-time setup phase, notwithstanding the number of nodes in the ecosystem that partake in the data collection of a certain epoch. Dropout-resistancy, trust-less key management, low-bandwidth and non-interactive nature of our construction make it ideal for many rapid-changing distributed real-world networks. Other than bandwidth efficiency, our scheme has also demonstrated efficiency in terms of computation overhead.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
PublisherIEEE
Pages640-645
Number of pages6
ISBN (Electronic)9781665453813
DOIs
Publication statusPublished - 2023
Publication typeA4 Article in conference proceedings
EventIEEE International Conference on Pervasive Computing and Communications Workshops - Atlanta, United States
Duration: 13 Mar 202317 Mar 2023

Publication series

Name IEEE International Conference on Pervasive Computing and Communications workshops
ISSN (Electronic)2766-8576

Conference

ConferenceIEEE International Conference on Pervasive Computing and Communications Workshops
Country/TerritoryUnited States
CityAtlanta
Period13/03/2317/03/23

Keywords

  • bandwidth-efficient
  • dropout-tolerant
  • dynamic groups
  • privacy-preserving aggregation
  • proxy re-encryption
  • time-series data

Publication forum classification

  • Publication forum level 0

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Health Informatics
  • Psychology (miscellaneous)

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