RCTD: Reputation-Constrained Truth Discovery in Sybil Attack Crowdsourcing Environment-Reference-Cited by-同舟云学术

RCTD: Reputation-Constrained Truth Discovery in Sybil Attack Crowdsourcing Environment

Published:2024-08-24 Issue: Volume:16 Page:1313-1324
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Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Jin Xing¹^ORCID,Gong Zhihai¹^ORCID,Jiang Jiuchuan²^ORCID,Wang Chao³^ORCID,Zhang Jian¹^ORCID,Wang Zhen⁴^ORCID

Affiliation:

1. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, Zhejiang, China

2. School of Information Engineering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, China

3. Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou, Zhejiang, China

4. School of Cyberspace, Hangzhou Dianzi University & Experimental Center of Data Science and Intelligent Decision-Making, Hangzhou Dianzi University, Hangzhou, Zhejiang, China

Funder

Key R&D Programs of Zhejiang

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

National Social Science Funds of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671803

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4. Gang Wang, Bolun Wang, Tianyi Wang, Ana Nika, Haitao Zheng, and Ben Y Zhao. Ghost riders: Sybil attacks on crowdsourced mobile mapping services. IEEE/ACM transactions on networking, 26(3):1123--1136, 2018.