一种基于双重信任检验的提高Skyline数据质量的采集方法
By employing a dual trust verification and probabilistic skyline calculation method, malicious workers are identified and eliminated, improving the data quality and security of the mobile crowdsourcing sensing platform, protecting privacy, and resolving issues related to malicious data and privacy protection.
CN115510394BActive Publication Date: 2026-07-17CENT SOUTH UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CENT SOUTH UNIV
- Filing Date
- 2022-09-26
- Publication Date
- 2026-07-17
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Figure CN115510394B_ABST
Abstract
本发明公开了一种基于双重信任检验的提高Skyline数据质量的采集方法，采用四种交叉验证的方法来获得工人可靠的信任评价，信任度未知工人与可信工人 / 可信用户的检验，信任度未知用户与可信用户 / 可信工人的检验。在此基础上，基于概率天际线计算进行工人选择，为报告数据选择高信任度和高任务相似度的工人，进而排除了与任务无关的低信任度工人，有效提高了Skyline采集数据的质量，保障了系统的安全性和隐私性。
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