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An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery

  • Published:2018-07-19 Issue: Volume: Page:
  • ISSN:
  • Container-title:Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
  • language:
  • Short-container-title:

Author:

Li Yaliang1,Miao Chenglin2,Su Lu2,Gao Jing2,Li Qi3,Ding Bolin4,Qin Zhan5,Ren Kui2

Affiliation:

1. Tencent Medical AI Lab, Palo Alto, CA, USA

2. State University of New York at Buffalo, Buffalo, NY, USA

3. University of Illinois at Urbana Champaign, Urbana, IL, USA

4. Alibaba Group, Bellevue, WA, USA

5. University of Texas at San Antonio, San Antonio, TX, USA

Funder

National Science Foundation

Publisher

ACM

Cited by 38 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. Data Poisoning Attacks and Defenses to LDP-Based Privacy-Preserving Crowdsensing;IEEE Transactions on Dependable and Secure Computing;2024-09

2. Privacy-Preserving Truth Discovery Based on Secure Multi-Party Computation in Vehicle-Based Mobile Crowdsensing;IEEE Transactions on Intelligent Transportation Systems;2024-07

3. Reliable and Streaming Truth Discovery in Blockchain-based Crowdsourcing;2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON);2023-09-11

4. Decentralized privacy-preserving truth discovery for crowd sensing;Information Sciences;2023-06

5. PrivTDSI: A Local Differentially Private Approach for Truth Discovery via Sampling and Inference;IEEE Transactions on Big Data;2023-04-01
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