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Add CITATION.cff file with metadata for software citation
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CITATION.cff

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cff-version: 1.2.0
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title: Privacy Pioneer
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message: >-
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If you use this software, please cite it using the
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metadata from this file.
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type: software
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authors:
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- given-names: Sebastian
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family-names: Zimmeck
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affiliation: Wesleyan University
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- given-names: Daniel
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family-names: Goldelman
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affiliation: Wesleyan University
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- given-names: Owen
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family-names: Kaplan
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affiliation: Wesleyan University
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- given-names: Logan
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family-names: Brown
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affiliation: Wesleyan University
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- given-names: Justin
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family-names: Casler
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affiliation: Wesleyan University
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- given-names: Judely
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family-names: Jean-Charles
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affiliation: Wesleyan University
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- given-names: Joe
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family-names: Champeau
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affiliation: Wesleyan University
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- given-names: Hamza
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family-names: Harkous
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affiliation: Google
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identifiers:
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- type: url
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value: >-
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https://petsymposium.org/popets/2024/popets-2024-0048.php
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description: PETS Publication
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repository-code: 'https://github.com/privacy-tech-lab/privacy-pioneer'
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abstract: >-
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Data collection by websites and their integrated third
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parties is often not transparent. We design privacy
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interfaces for the browser to help people understand who
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is collecting which data from them. In a proof of concept
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browser extension, Privacy Pioneer , we implement a
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privacy popup, a privacy history interface, and a
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watchlist to notify people when their data is collected.
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For detecting location data collection, we develop a
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machine learning model based on TinyBERT, which reaches an
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average F1 score of 0.94. We supplement our model with
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deterministic methods to detect trackers, collection of
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personal data, and other monetization techniques. In a
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usability study with 100 participants 82% found Privacy
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Pioneer easy to understand and 90% found it useful
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indicating the value of privacy interfaces directly
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integrated in the browser
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keywords:
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- Web Privacy
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- Data Transparency
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- Privacy Dashboards
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- Notice and Choice
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- Consent
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- Privacy Labels
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- Usability
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- Privacy Enhancing Technologies
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- Web Traffic Analysis
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- BERT
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- Machine Learning
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license: CC-BY-NC-SA-4.0
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commit: 7c1ab1c
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version: v1.2.2
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date-released: '2023-11-19'

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