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2020 | OriginalPaper | Buchkapitel

Blind Face Retrieval for Mobile Users

verfasst von : Xin Jin, Shiming Ge, Chenggen Song, Le Wu, Hongbo Sun

Erschienen in: 2nd EAI International Conference on Robotic Sensor Networks

Verlag: Springer International Publishing

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Abstract

Recently, cloud storage and processing have been widely adopted. Mobile users in one family or one team may automatically backup their photos to the same shared cloud storage space. The powerful face detector trained and provided by a 3rd party may be used to retrieve the photo collection which contains a specific group of persons from the cloud storage server. However, the privacy of the mobile users may be leaked to the cloud server providers. In the meanwhile, the copyright of the face detector should be protected. Thus, in this paper, we propose a protocol of privacy preserving face retrieval in the cloud for mobile users, which protects the user photos and the face detector simultaneously. The cloud server only provides the resources of storage and computing and cannot learn anything from the user photos and the face detector. We test our protocol inside several families and classes. The experimental results reveal that our protocol can successfully retrieve the proper photos from the cloud server and protect the user photos and the face detector.

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Metadaten
Titel
Blind Face Retrieval for Mobile Users
verfasst von
Xin Jin
Shiming Ge
Chenggen Song
Le Wu
Hongbo Sun
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-17763-8_11

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