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Efficient privacy-preserving facial expression classification

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journal contribution
posted on 02.02.2017 by Yogachandran Rahulamathavan, Muttukrishnan Rajarajan
This paper proposes an efficient algorithm to perform privacy-preserving (PP) facial expression classification (FEC) in the client-server model. The server holds a database and offers the classification service to the clients. The client uses the service to classify the facial expression (FaE) of subject. It should be noted that the client and server are mutually untrusted parties and they want to perform the classification without revealing their inputs to each other. In contrast to the existing works, which rely on computationally expensive cryptographic operations, this paper proposes a lightweight algorithm based on the randomization technique. The proposed algorithm is validated using the widely used JAFFE and MUG FaE databases. Experimental results demonstrate that the proposed algorithm does not degrade the performance compared to existing works. However, it preserves the privacy of inputs while improving the computational complexity by 120 times and communication complexity by 31 percent against the existing homomorphic cryptography based approach.

History

School

  • Loughborough University London

Published in

IEEE Transactions on Dependable and Secure Computing

Volume

PP

Issue

99

Citation

RAHULAMATHAVAN, Y. and RAJARAJAN, M., 2015. Efficient privacy-preserving facial expression classification. IEEE Transactions on Dependable and Secure Computing, PP (99).

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2015

Notes

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISSN

1545-5971

Language

en

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