Non-interactive privacy-preserving truth discovery in crowd sensing applications

Xiaoting Tang, Cong Wang, Xingliang Yuan, Qian Wang

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

8 Citations (Scopus)

Abstract

In crowd sensing, truth discovery (TD) refers to finding reliable information from noisy/biased data collected from different providers. To protect providers' data while enabling truth distillation, privacy-preserving truth discovery (PPTD) has received wide attention recently. However, all existing approaches require iterative interaction between server(s) and individual providers, which inevitably demand all providers to be always online. Otherwise, the protocol would fail or expose extra provider information. In this paper, we design and implement the first non-interactive PPTD system that completely removes the online requirement with strong privacy guarantees. Our framework follows the same two-server model from the best-known prior solution, and leverages Yao's Garbled Circuit (GC). Yet, we devise non-trivial speedup techniques for TD-optimized implementation. Firstly, we identify reusable computations in TD to accelerate the circuit generation. Secondly, we securely evaluate the burdensome non-linear functions in TD via customized approximation with accuracy and improved efficiency. Thirdly, we reduce the online execution time by bridging together latest advancements of component-based GC and various computations needed in TD. Unlike prior arts, our framework does not reveal any intermediate results, and further supports 'late-join' providers without protocol suspension/restart. The practical performance of our proof-of-concept implementation is verified through extensive evaluations.

Original languageEnglish
Title of host publicationIEEE INFOCOM 2018 - IEEE Conference on Computer Communications
EditorsShiwen Mao, Tommaso Melodia, Prasun Sinha
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1988-1996
Number of pages9
ISBN (Electronic)9781538641286
ISBN (Print)9781538641293
DOIs
Publication statusPublished - 2018
EventIEEE Conference on Computer Communications 2018 - Honolulu, United States of America
Duration: 15 Apr 201819 Apr 2018
https://infocom2018.ieee-infocom.org/

Conference

ConferenceIEEE Conference on Computer Communications 2018
Abbreviated titleINFOCOM 2018
CountryUnited States of America
CityHonolulu
Period15/04/1819/04/18
Internet address

Cite this

Tang, X., Wang, C., Yuan, X., & Wang, Q. (2018). Non-interactive privacy-preserving truth discovery in crowd sensing applications. In S. Mao, T. Melodia, & P. Sinha (Eds.), IEEE INFOCOM 2018 - IEEE Conference on Computer Communications (pp. 1988-1996). [8486371] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/INFOCOM.2018.8486371