Please use this identifier to cite or link to this item:
http://arks.princeton.edu/ark:/88435/dsp01j9602293q| Title: | Scaling OpenWPM |
| Authors: | Beaulieu, Nicholas |
| Advisors: | Narayanan, Arvind |
| Department: | Computer Science |
| Class Year: | 2015 |
| Abstract: | The Open Web Privacy Measurements platform has been successful at providing a framework for black-box testing of the internet. OpenWPM produces cross-sectional studies which are di cult to distribute. We propose architectural changes to Open- WPM that enable both longitudinal studies and single click reproduction. By redesign- ing the storage and analysis components to scale horizontally, the architecture can scale to growing needs. We encapsulate the added complexity in static containers which are deployed using scripts in order to reproduce studies in under ten minutes. |
| Extent: | 21 pages |
| URI: | http://arks.princeton.edu/ark:/88435/dsp01j9602293q |
| Type of Material: | Princeton University Senior Theses |
| Language: | en_US |
| Appears in Collections: | Computer Science, 1987-2023 |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| PUTheses2015-Beaulieu_Nicholas.pdf | 291 kB | Adobe PDF | Request a copy |
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