Skip to search boxSkip to navigationSkip to main content

Information-Theoretically Secure and Highly E!icient Search and Row Retrieval

  • Shantanu Sharma
    ,
  • Yin Li
    ,
  • Sharad Mehrotra
    ,
  • ,
  • Komal Kumari
    ,
  • Swagnik Roychoudhury
Scholary Output:
Contribution to journal
Conference article
Peer-review

Related Event

Title

49th International Conference on Very Large Data Bases, VLDB 2023

Event type

Conference

Date

08/28/2023 - 09/01/2023

Location

VancouverCanada

Abstract

Information-theoretic or unconditional security provides the highest level of security - independent of the computational capability of an adversary. Secret-sharing techniques achieve information- theoretic security by splitting a secret into multiple parts (called shares) and storing the shares across non-colluding servers. How-ever, secret-sharing-based solutions suffer from high overheads due to multiple communication rounds among servers and/or information leakage due to access-patterns (i.e., the identity of rows satisfying a query) and volume (i.e., the number of rows satisfying a query). We propose S2, an information-theoretically secure approach that uses both additive and multiplicative secret-sharing, to efficiently support a large class of selection queries involving conjunctive, disjunctive, and range conditions. Two major contributions of S2 are: (i) a new search algorithm using additive shares based on fingerprints, which were developed for string-matching over cleartext; and (ii) two row retrieval algorithms: one is based on multiplicative shares and another is based on additive shares. !2 does not require communication among servers storing shares and does not reveal any information to an adversary based on access-patterns and volume.

Publication Information

Output type

Scholary Output:
Contribution to journal
Conference article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 2391-2403 (13 pages)

Journal (Volume, Issue Number)

Proceedings of the VLDB Endowment (Volume 16, Issue 10)

Publication milestones

  • Published - 2023

Publication status

Published - 2023

ISSN

2150-8097

Publication IDs

  • Scopus: 85172729794

Publication metrics

Metrics

Fractional count
1
Fractional count
0.17
Fractional count
5
Fractional count
0.83
Fractional count
1
Fractional count
1
Scopus
citations

PlumX, opens in new tab

Citation count
2
Captures
5

Funding Details

We are thankful to the reviewers. Yin Li was funded by National Key Research and Development Program of China under Grant 2021YFB3101300. Sharad Mehrotra was partially funded by the research sponsored by DARPA under agreement number FA8750-16-2-0021 and NSF Grants No. 1952247, 2133391, 2032525, and 2008993. Nisha Panwar was partially funded by NSF Grants No. 2131538.
FundersFunding numbers
NSF
2008993, 2131538, 1952247, 2133391, 2032525
NKRDPC
2021YFB3101300
DARPA
FA8750-16-2-0021