research-article

GSHADE: faster privacy-preserving distance computation and biometric identification

Authors:

Julien Bringer,

Herve Chabanne,

Thomas Schneider,

Michael ZohnerAuthors Info & Claims

IH&MMSec '14: Proceedings of the 2nd ACM workshop on Information hiding and multimedia security

Pages 187 - 198

https://doi.org/10.1145/2600918.2600922

Published: 11 June 2014 Publication History

Abstract

At WAHC'13, Bringer et al. introduced a protocol called SHADE for secure and efficient Hamming distance computation using oblivious transfer only. In this paper, we introduce a generalization of the SHADE protocol, called GSHADE, that enables privacy-preserving computation of several distance metrics, including (normalized) Hamming distance, Euclidean distance, Mahalanobis distance, and scalar product. GSHADE can be used to efficiently compute one-to-many biometric identification for several traits (iris, face, fingerprint) and benefits from recent optimizations of oblivious transfer extensions. GSHADE allows identification against a database of 1000 Eigenfaces in 1.28 seconds and against a database of 10000 IrisCodes in 17.2 seconds which is more than 10 times faster than previous works.

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Cited By

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EdalatNejad KLueks WSukaitis JNarbel VMarelli MTroncoso C(2024)Janus: Safe Biometric Deduplication for Humanitarian Aid Distribution2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00116(655-672)Online publication date: 19-May-2024
https://doi.org/10.1109/SP54263.2024.00116
Peng ZShi RDing RZhang F(2024)A novel quantum protocol for secure hamming distance computationQuantum Information Processing10.1007/s11128-024-04357-223:5Online publication date: 29-Apr-2024
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Index Terms

GSHADE: faster privacy-preserving distance computation and biometric identification
1. Security and privacy
  1. Cryptography
  2. Systems security
    1. Operating systems security

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cover image ACM Conferences

IH&MMSec '14: Proceedings of the 2nd ACM workshop on Information hiding and multimedia security

June 2014

212 pages

ISBN:9781450326476

DOI:10.1145/2600918

Conference Chair:
Andreas Unterweger
University of Salzburg, Austria
,
General Chair:
Andreas Uhl
University of Salzburg, Austria
,
Program Chairs:
Stefan Katzenbeisser
TU Darmstadt, Germany
,
Roland Kwitt
University of Salzburg, Austria
,
Alessandro Piva
University of Florence, Italy

Copyright © 2014 ACM.

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Published: 11 June 2014

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Seventh Framework Programme

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IH&MMSec '14

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SIGMM

IH&MMSec '14: ACM Information Hiding and Multimedia Security Workshop

June 11 - 13, 2014

Salzburg, Austria

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IH&MMSec '14 Paper Acceptance Rate 24 of 64 submissions, 38%;

Overall Acceptance Rate 128 of 318 submissions, 40%

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Cited By

Gunasinghe HAtallah MBertino E(2024)PEBASI: A Privacy preserving, Efficient Biometric Authentication Scheme based on IrisesACM Transactions on Privacy and Security10.1145/3677017Online publication date: 11-Jul-2024
https://doi.org/10.1145/3677017
EdalatNejad KLueks WSukaitis JNarbel VMarelli MTroncoso C(2024)Janus: Safe Biometric Deduplication for Humanitarian Aid Distribution2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00116(655-672)Online publication date: 19-May-2024
https://doi.org/10.1109/SP54263.2024.00116
Peng ZShi RDing RZhang F(2024)A novel quantum protocol for secure hamming distance computationQuantum Information Processing10.1007/s11128-024-04357-223:5Online publication date: 29-Apr-2024
https://doi.org/10.1007/s11128-024-04357-2
Wu DLiang BLu ZDing J(2024)Efficient Secure Multi-party Computation for Multi-dimensional Arithmetics and Its Application in Privacy-Preserving Biometric IdentificationCryptology and Network Security10.1007/978-981-97-8013-6_1(3-25)Online publication date: 2-Oct-2024
https://doi.org/10.1007/978-981-97-8013-6_1
Manvi PDesai ASrinathan KNamboodiri A(2023)S-BAN: Secure Biometric Authentication using NoiseProceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing10.1145/3627631.3627638(1-9)Online publication date: 15-Dec-2023
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Polireddi NSuryadevara MVenkata SRangineni SKoduru SAgal S(2023)A Novel Study on Data Science for Data Security and Data Integrity with Enhanced Heuristic Scheduling in Cloud2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)10.1109/ICACRS58579.2023.10404262(1862-1868)Online publication date: 11-Dec-2023
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Verma GKanrar S(2022)A novel model to enhance the data security in cloud environmentMultiagent and Grid Systems10.3233/MGS-22036118:1(45-63)Online publication date: 1-Jan-2022
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Hu MWu DWu RShi ZChen MZhou Y(2022) RAP : A Light-Weight Privacy-Preserving Framework for Recommender Systems IEEE Transactions on Services Computing10.1109/TSC.2021.306503515:5(2969-2981)Online publication date: 1-Sep-2022
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Zhao FLi ZWang H(2022)PPCNN: An efficient privacy‐preserving CNN training and inference frameworkInternational Journal of Intelligent Systems10.1002/int.2303037:12(10988-11018)Online publication date: 23-Aug-2022
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Xie HGuo YJia X(2021)A Privacy-Preserving Online Ride-Hailing System Without Involving a Third Trusted ServerIEEE Transactions on Information Forensics and Security10.1109/TIFS.2021.306583216(3068-3081)Online publication date: 2021
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