3.8 Proceedings Paper

Garbled Circuits with Sublinear Evaluator

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出版社

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-031-06944-4_2

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资金

  1. NSF [CNS-2001096, CNS-1764025, CNS-1718074, 1909769]
  2. Facebook research award
  3. Cisco research award
  4. Georgia Tech's IISP cybersecurity seed funding (CSF) award
  5. DARPA [HR0011-20-2-0025, HR001120C0087]
  6. US-Israel BSF [2015782]
  7. Google Faculty Award
  8. IBM Faculty Research Award
  9. Xerox Faculty Research Award
  10. OKAWA Foundation Research Award
  11. B. John Garrick Foundation Award
  12. Teradata Research Award
  13. Lockheed-Martin Research Award
  14. JP Morgan Faculty Award
  15. Sunday Group
  16. Division Of Computer and Network Systems
  17. Direct For Computer & Info Scie & Enginr [1909769] Funding Source: National Science Foundation

向作者/读者索取更多资源

This article presents a garbling scheme called GCWise, which achieves fully sublinear evaluation by including the evaluator's work within the sublinearity scope. The application of garbled PIR is also demonstrated, which enables non-interactive and sublinear access to private elements in a database.
A recent line of work, Stacked Garbled Circuit (SGC), showed that Garbled Circuit (GC) can be improved for functions that include conditional behavior. SGC relieves the communication bottleneck of 2PC by only sending enough garbled material for a single branch out of the b total branches. Hence, communication is sublinear in the circuit size. However, both the evaluator and the generator pay in computation and perform at least factor log b extra work as compared to standard GC. We extend the sublinearity of SGC to also include the work performed by the GC evaluator E; thus we achieve a fully sublinear E, which is essential when optimizing for the online phase. We formalize our approach as a garbling scheme called GCWise: GC WIth Sublinear Evaluator. We show one attractive and immediate application, Garbled PIR, a primitive that marries GC with Private Information Retrieval. Garbled PIR allows the GC to non-interactively and sublinearly access a privately indexed element from a publicly known database, and then use this element in continued GC evaluation.

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