SecDR: Enabling Secure, Efficient, and Accurate Data Recovery for Mobile Crowdsensing-Reference-Cited by-同舟云学术

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SecDR: Enabling Secure, Efficient, and Accurate Data Recovery for Mobile Crowdsensing

Published:2023 Issue: Volume: Page:1-15
ISSN:1545-5971
Container-title:IEEE Transactions on Dependable and Secure Computing
language:
Short-container-title:IEEE Trans. Dependable and Secure Comput.

Author:

Zheng Yifeng¹^ORCID,Zhou Menglun¹,Wang Songlei¹^ORCID,Huang Hejiao¹^ORCID,Jia Xiaohua¹^ORCID,Yi Xun²^ORCID,Wang Cong³^ORCID

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Guangdong, China

2. School of Computing Technologies, RMIT University, Melbourne, VIC, Australia

3. Department of Computer Science, City University of Hong Kong, Hong Kong, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8858/4358699/10083214.pdf?arnumber=10083214

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Privacy-security oriented chaotic compressed sensing data collection in edge-assisted mobile crowd sensing;Ad Hoc Networks;2024-07

2. Privacy Preservation of Electronic Health Records in the Modern Era: A Systematic Survey;ACM Computing Surveys;2024-04-26

3. BTV-CMAB: A Bi-Directional Trust Verification-Based Combinatorial Multiarmed Bandit Scheme for Mobile Crowdsourcing;IEEE Internet of Things Journal;2024-01-15

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