Confidential Truth Finding with Multi-Party Computation - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2023

Confidential Truth Finding with Multi-Party Computation

Abstract

Federated knowledge discovery and data mining are challenged to assess the trustworthiness of data originating from autonomous sources while protecting confidentiality and privacy. Truth-finding algorithms help corroborate data from disagreeing sources. For each query it receives, a truth-finding algorithm predicts a truth value of the answer, possibly updating the trustworthiness factor of each source. Few works, however, address the issues of confidentiality and privacy. We devise and present a secure secret-sharing-based multi-party computation protocol for pseudo-equality tests that are used in truth-finding algorithms to compute additions depending on a condition. The protocol guarantees confidentiality of the data and privacy of the sources. We also present a variants of a truth-finding algorithm that would make the computation faster when executed using secure multi-party computation. We empirically evaluate the performance of the proposed protocol on a state-of-the-art truth-finding algorithm, 3-Estimates, and compare it with that of the baseline plain algorithm. The results confirm that the secret-sharing-based secure multi-party algorithms are as accurate as the corresponding baselines but for proposed numerical approximations that significantly reduce the efficiency loss incurred.
Fichier principal
Vignette du fichier
main.pdf (310.83 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04139281 , version 1 (23-06-2023)

Licence

Identifiers

  • HAL Id : hal-04139281 , version 1

Cite

Angelo Saadeh, Pierre Senellart, Stéphane Bressan. Confidential Truth Finding with Multi-Party Computation. DEXA 2023 - 34th International Conference on Database and Expert Systems Applications, Aug 2023, Penang, Malaysia. ⟨hal-04139281⟩
82 View
34 Download

Share

Gmail Mastodon Facebook X LinkedIn More