Sybil Defense in Crowdsourcing Platforms

Author:

Yuan Dong1,Li Guoliang2,Li Qi1,Zheng Yudian3

Affiliation:

1. Tsinghua University, Shenzhen, China

2. Tsinghua University, Beijing, China

3. University of Hong Kong, Hong Kong, China

Publisher

ACM

Cited by 22 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. Provably Secure Decisions Based on Potentially Malicious Information;IEEE Transactions on Dependable and Secure Computing;2024-09

2. RCTD: Reputation-Constrained Truth Discovery in Sybil Attack Crowdsourcing Environment;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. Truth Discovery Against Disguised Attack Mechanism in Crowdsourcing;Lecture Notes in Computer Science;2024

4. Efficient Privacy-Preserving Truth Discovery and Copy Detection in Crowdsourcing;Lecture Notes in Computer Science;2024

5. Effectiveness of Malicious Behavior and Its Impact on Crowdsourcing;Computer Supported Cooperative Work and Social Computing;2023

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