Fundamental Limits of Anonymous Statistical Inference: Privacy-Preserving Crowdsourcing and Heterogeneous Sensor Networks
碩士 === 國立臺灣大學 === 電信工程學研究所 === 107 === In this thesis, we propose two treatments to overcome the anonymity issue in privacy-preserving crowdsourcing: group recovery with golden questions and anonymous hypothesis testing. Consider a data set comprising n items, each of which represents a worker and h...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2017
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| Online Access: | http://ndltd.ncl.edu.tw/handle/tyauuw |