Publication: Quantifying Attributes of Privacy Policies Using Contextual Integrity
| datacite.rights | restricted | |
| dc.contributor.advisor | Mittal, Prateek | |
| dc.contributor.author | Liao, Michael | |
| dc.date.accessioned | 2017-07-24T13:13:11Z | |
| dc.date.accessioned | 2026-09-29T22:34:48Z | |
| dc.date.available | 2017-07-24T13:13:11Z | |
| dc.date.available | 2026-09-29T22:34:48Z | |
| dc.date.created | 2017-05-08 | |
| dc.date.issued | 2017-5-8 | |
| dc.description.abstract | Identifying vulnerabilities in systems is a critical step in safeguarding users’ privacy but is often only accomplished after an adversary exploiting an existing flaw in a system. Contextual Integrity provides a framework for understanding information flows which are appropriate to the privacy norms associated with a given context. By using the framework which Contextual Integrity affords, I discovered a way to potentially model the privacy characteristics of a service’s privacy policy in a systematic and quantitative manner. This characterization may render privacy policies more transparent for users and assist developers in making their services more secure. | en_US |
| dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01z316q422b | |
| dc.identifier.uri | https://theses-dissertations.princeton.edu/handle/88435/dsp01z316q422b | |
| dc.language.iso | en_US | en_US |
| dc.title | Quantifying Attributes of Privacy Policies Using Contextual Integrity | en_US |
| dc.type | Princeton University Senior Theses | |
| dspace.entity.type | Publication | |
| pu.contributor.advisorid | 960944224 | |
| pu.contributor.authorid | 960877196 | |
| pu.date.classyear | 2017 | en_US |
| pu.department | Electrical Engineering | en_US |
| pu.pdf.coverpage | SeniorThesisCoverPage |
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