Spatio-Temporal Similarity based Privacy-Preserving Worker Selection in Mobile Crowdsensing-Reference-Cited by-同舟云学术

Spatio-Temporal Similarity based Privacy-Preserving Worker Selection in Mobile Crowdsensing

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Global Communications Conference (GLOBECOM)
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Author:

Zhang Xichen¹,Lu Rongxing¹,Ray Suprio¹,Shao Jun²,Ghorbani Ali A.¹

Affiliation:

1. University of New Brunswick,Canadian Institute for Cybersecurity, Faculty of Computer Science,Fredericton,NB,Canada

2. School of Computer and Information Engineering, Zhejiang Gongshang University,Hangzhou,China,310018

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9685019/9685006/09685450.pdf?arnumber=9685450

Reference7 articles.

1. Task Allocation in Dependency-aware Spatial Crowdsourcing

2. Preserving location pri-vacy for outsourced most-frequent item query in mobile crowdsensing;zhang;IEEE Internet of Things Journal,2021

3. A Simple Public-Key Cryptosystem with a Double Trapdoor Decryption Mechanism and Its Applications

4. Privacy-Preserving Online Task Assignment in Spatial Crowdsourcing with Untrusted Server

5. Efficient contact similarity query over uncertain trajectories;zhang;Proceedings of the 24th International Conference on Extending Database Technology EDBT 2021,2021

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