2026-09-20T09:42:42Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1445582022-08-30T03:08:06Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Madden, Samuel
Cao, Lei
Xu, Helen J.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-08-29T15:55:46Z
2022-08-29T15:55:46Z
2022-05
2022-05-27T16:18:35.269Z
https://hdl.handle.net/1721.1/144558
Data privacy is a fundamental ethical goal. We must aim for innovating without exploiting. In order to provide formal privacy guarantees, differential privacy has been the central method of implementing database privacy. However, there are many barriers to widespread adoption. General methods lack accuracy and more innovative methods lack applicability beyond a specific kind of data or query. This project aims to create an effective differentially private system that provides an identical user experience to using raw data and redefines utility in database privacy to focus on the user experience.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
A Universally Applicable Differential Privacy System: Redefining Utility in Database Privacy to Prioritize User Experience
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>Data privacy is a fundamental ethical goal. We must aim for innovating without exploiting. In order to provide formal privacy guarantees, differential privacy has been the central method of implementing database privacy. However, there are many barriers to widespread adoption. General methods lack accuracy and more innovative methods lack applicability beyond a specific kind of data or query. This project aims to create an effective differentially private system that provides an identical user experience to using raw data and redefines utility in database privacy to focus on the user experience.</Abstract>
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