Soft Computing

, Volume 23, Issue 23, pp 12813–12820 | Cite as

Secure face retrieval for group mobile users

  • Xin Jin
  • Yujie Li
  • Shiming GeEmail author
  • Chenggen Song
  • Le Wu
  • Xinghui Zhou
Methodologies and Application


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 of 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.


Privacy preserving Face retrieval Cloud computing 



This work is partially supported by the National Natural Science Foundation of China (Grant Nos. 61772047, 61772513), the Open Funds of CETC Big Data Research Institute Co.,Ltd., (Grant No. W-2018022), the Science and Technology Project of the State Archives Administrator (Grant No. 2015-B-10), and the Fundamental Research Funds for the Central Universities (Grant Nos. 328201803, 328201801).

Compliance with ethical standards

Conflict of interest

None of the authors declare that he/she has conflict of interest.

Human or animals rights

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Beijing Electronic Science and Technology InstituteBeijingChina
  2. 2.CETC Big Data Research Institute Co.,Ltd.GuiyangChina
  3. 3.Kyushu Institute of Technology, KITKitakyushuJapan
  4. 4.Fukuoka University, FUFukuokaJapan
  5. 5.Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  6. 6.OracleChain TechnologyBeijingChina

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