has been cited by the following article(s):
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[1]
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Matching as You Want: A Decentralized, Flexible, and Efficient Realization for Crowdsourcing With Dual-Side Privacy
IEEE Transactions on Network Science and Engineering,
2025
DOI:10.1109/TNSE.2024.3522914
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[2]
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VP2-Match: Verifiable Privacy-Aware and Personalized Crowdsourcing Task Matching via Blockchain
IEEE Transactions on Mobile Computing,
2024
DOI:10.1109/TMC.2024.3369085
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[3]
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Bilateral Secure and Decentralized Crowdsourcing Task Matching Atop Consortium Blockchain
2024 IEEE International Conference on Blockchain (Blockchain),
2024
DOI:10.1109/Blockchain62396.2024.00045
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[4]
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An integrated security approach for vehicular networks in smart cities
Transactions on Emerging Telecommunications Technologies,
2023
DOI:10.1002/ett.4757
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[5]
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An integrated security approach for vehicular networks in smart cities
Transactions on Emerging Telecommunications Technologies,
2023
DOI:10.1002/ett.4757
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[6]
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A Triple Real-Time Trajectory Privacy Protection Mechanism Based on Edge Computing and Blockchain in Mobile Crowdsourcing
IEEE Transactions on Mobile Computing,
2023
DOI:10.1109/TMC.2022.3187047
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[7]
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Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices
IEEE Internet of Things Journal,
2021
DOI:10.1109/JIOT.2020.3017377
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