Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01z316q422b
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Mittal, Prateek | - |
dc.contributor.author | Liao, Michael | - |
dc.date.accessioned | 2017-07-24T13:13:11Z | - |
dc.date.available | 2017-07-24T13:13:11Z | - |
dc.date.created | 2017-05-08 | - |
dc.date.issued | 2017-5-8 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/dsp01z316q422b | - |
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.language.iso | en_US | en_US |
dc.title | Quantifying Attributes of Privacy Policies Using Contextual Integrity | en_US |
dc.type | Princeton University Senior Theses | - |
pu.date.classyear | 2017 | en_US |
pu.department | Electrical Engineering | en_US |
pu.pdf.coverpage | SeniorThesisCoverPage | - |
pu.contributor.authorid | 960877196 | - |
pu.contributor.advisorid | 960944224 | - |
Appears in Collections: | Electrical Engineering, 1932-2020 |
Files in This Item:
File | Size | Format | |
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ELE498LiaoThesis.pdf | 1.05 MB | Adobe PDF | Request a copy |
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