Privacy-preserving data aggregation computing in cyber-physical social systems

Jiahui Yu, Kun Wang, Deze Zeng, Chunsheng Zhu, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

In cyber-physical social systems (CPSS), a group of volunteers report data about the physical environment through their cyber devices and data aggregation is widely utilized. An important issue in data aggregation for CPSS is to protect users' privacy. In this article, we use bitwise XOR and propose a bit-choosing algorithm to realize privacy-preserving min, k-th min, and percentile computation. By our algorithm, the aggregator can confirm whether a user's data value is equal to certain value or within certain scale. Consequently, it is also possible to count the number of users satisfying given conditions. Our bit-choosing algorithm makes sure that the users send non-repetition replies to the aggregator to raise the aggregation accuracy. We analyze the communication cost and the achievable accuracy of our algorithm. Via performance comparison against existing protocols, the efficiency and accuracy of our algorithm are verified.

Original languageEnglish
Article number8
JournalACM Transactions on Cyber-Physical Systems
Volume3
Issue number1
DOIs
Publication statusPublished - Aug 2018

Keywords

  • Cyber-physical social systems
  • Data aggregation
  • Privacy-preserving

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Human-Computer Interaction
  • Control and Optimization

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