Noninteractive Lightweight Privacy-Preserving Auditing on Images in Mobile Crowdsourcing Networks
Joint Authors
Guo, Xiaojun
Zhang, Chunyu
Zhang, Juan
Wan, Changsheng
Chen, Yongyong
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-25
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
To determine whether images on the crowdsourcing server meet the mobile user’s requirement, an auditing protocol is desired to check these images.
However, before paying for images, the mobile user typically cannot download them for checking.
Moreover, since mobiles are usually low-power devices and the crowdsourcing server has to handle a large number of mobile users, the auditing protocol should be lightweight.
To address the above security and efficiency issues, we propose a novel noninteractive lightweight privacy-preserving auditing protocol on images in mobile crowdsourcing networks, called NLPAS.
Since NLPAS allows the mobile user to check images on the crowdsourcing server without downloading them, the newly designed protocol can provide privacy protection for these images.
At the same time, NLPAS uses the binary convolutional neural network for extracting features from images and designs a novel privacy-preserving Hamming distance computation algorithm for determining whether these images on the crowdsourcing server meet the mobile user’s requirement.
Since these two techniques are both lightweight, NLPAS can audit images on the crowdsourcing server in a privacy-preserving manner while still enjoying high efficiency.
Experimental results show that NLPAS is feasible for real-world applications.
American Psychological Association (APA)
Zhang, Juan& Wan, Changsheng& Zhang, Chunyu& Guo, Xiaojun& Chen, Yongyong. 2020. Noninteractive Lightweight Privacy-Preserving Auditing on Images in Mobile Crowdsourcing Networks. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1208611
Modern Language Association (MLA)
Zhang, Juan…[et al.]. Noninteractive Lightweight Privacy-Preserving Auditing on Images in Mobile Crowdsourcing Networks. Security and Communication Networks No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1208611
American Medical Association (AMA)
Zhang, Juan& Wan, Changsheng& Zhang, Chunyu& Guo, Xiaojun& Chen, Yongyong. Noninteractive Lightweight Privacy-Preserving Auditing on Images in Mobile Crowdsourcing Networks. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1208611
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208611