EPRICE: An Efficient and Privacy-Preserving Real-Time Incentive System for Crowdsensing in Industrial Internet of Things-Reference-Cited by-同舟云学术

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EPRICE: An Efficient and Privacy-Preserving Real-Time Incentive System for Crowdsensing in Industrial Internet of Things

Published:2023-09-01 Issue:9 Volume:72 Page:2482-2495
ISSN:0018-9340
Container-title:IEEE Transactions on Computers
language:
Short-container-title:IEEE Trans. Comput.

Author:

Feng Qi¹^ORCID,He Debiao¹^ORCID,Luo Min¹^ORCID,Huang Xinyi²^ORCID,Choo Kim-Kwang Raymond³^ORCID

Affiliation:

1. School of Cyber Science and Engineering, Wuhan University, Wuhan, Hubei, China

2. Artificial Intelligence Thrust, Information Hub, Hong Kong University of Science and Technology(Guangzhou), Guangzhou, Guangdong Province, China

3. Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio, TX, USA

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Special Project on Science and Technology Program of Hubei Provience

Cloud Technology Endowed Professorship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/12/10213258/10057980.pdf?arnumber=10057980

Reference38 articles.

1. Privacy-Aware and Efficient Mobile Crowdsensing with Truth Discovery

2. Efficient Secure Two-Party Protocols

3. RPPTD: Robust Privacy-Preserving Truth Discovery Scheme

4. Security and Composition of Multiparty Cryptographic Protocols

5. Privacy-Preserving Truth Discovery in Crowd Sensing Systems

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1. PODI: A Private Object Detection Inference framework for autonomous vehicles;Knowledge-Based Systems;2024-10

2. Group Coding Location Privacy Protection Method Based on Differential Privacy in Crowdsensing;IEEE Internet of Things Journal;2024-09-01

3. TB-HQ: An Incentive Mechanism for High-Quality Cooperation in Crowdsensing;Electronics;2024-03-26

4. HiBid: A Cross-Channel Constrained Bidding System with Budget Allocation by Hierarchical Offline Deep Reinforcement Learning;IEEE Transactions on Computers;2023

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