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Full-Text Articles in Physical Sciences and Mathematics
Practical Methods For High-Dimensional Data Publication With Differential Privacy, Ryan H. Mckenna
Practical Methods For High-Dimensional Data Publication With Differential Privacy, Ryan H. Mckenna
Doctoral Dissertations
In recent years, differential privacy has seen significant growth, and has been widely embraced as the dominant privacy definition by the research community. Much progress has been made on designing theoretically principled and practically sound privacy mechanisms. There have even been some real-world deployments of differential privacy, although it has not yet seen widespread adoption. One challenge is that for some problems, there is a gap between the privacy budget required to have a meaningful privacy guarantee and to retain data utility. A second challenge is that many privacy mechanisms have trouble scaling to high-dimensional data, limiting their applicability to …
Towards Practical Differentially Private Mechanism Design And Deployment, Dan Zhang
Towards Practical Differentially Private Mechanism Design And Deployment, Dan Zhang
Doctoral Dissertations
As the collection of personal data has increased, many institutions face an urgent need for reliable protection of sensitive data. Among the emerging privacy protection mechanisms, differential privacy offers a persuasive and provable assurance to individuals and has become the dominant model in the research community. However, despite growing adoption, the complexity of designing differentially private algorithms and effectively deploying them in real-world applications remains high. In this thesis, we address two main questions: 1) how can we aid programmers in developing private programs with high utility? and 2) how can we deploy differentially private algorithms to visual analytics systems? …