CITATION.cff

cff-version: 1.2.0
title: Website Data Transparency in the Browser
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Sebastian
    family-names: Zimmeck
    affiliation: Wesleyan University
  - given-names: Daniel
    family-names: Goldelman
    affiliation: Wesleyan University
  - given-names: Owen
    family-names: Kaplan
    affiliation: Wesleyan University
  - given-names: Logan
    family-names: Brown
    affiliation: Wesleyan University
  - given-names: Justin
    family-names: Casler
    affiliation: Wesleyan University
  - given-names: Judely
    family-names: Jean-Charles
    affiliation: Wesleyan University
  - given-names: Joe
    family-names: Champeau
    affiliation: Wesleyan University
  - given-names: Hamza
    family-names: Harkous
    affiliation: Google
identifiers:
  - type: url
    value: >-
      https://petsymposium.org/popets/2024/popets-2024-0048.php
    description: 24th Privacy Enhancing Technologies Symposium (PETS)
repository-code: 'https://github.com/privacy-tech-lab/privacy-pioneer'
abstract: >-
  Data collection by websites and their integrated third
  parties is often not transparent. We design privacy
  interfaces for the browser to help people understand who
  is collecting which data from them. In a proof of concept
  browser extension, Privacy Pioneer , we implement a
  privacy popup, a privacy history interface, and a
  watchlist to notify people when their data is collected.
  For detecting location data collection, we develop a
  machine learning model based on TinyBERT, which reaches an
  average F1 score of 0.94. We supplement our model with
  deterministic methods to detect trackers, collection of
  personal data, and other monetization techniques. In a
  usability study with 100 participants 82% found Privacy
  Pioneer easy to understand and 90% found it useful
  indicating the value of privacy interfaces directly
  integrated in the browser.
keywords:
  - Web Privacy
  - Data Transparency
  - Privacy Dashboards
  - Notice and Choice
  - Consent
  - Privacy Labels
  - Usability
  - Privacy Enhancing Technologies
  - Web Traffic Analysis
  - BERT
  - Machine Learning
license: CC-BY-4.0-Deed
commit: 7c1ab1c
version: v1.2.1
date-released: '2023-07-11'
booktitle: 24th Privacy Enhancing Technologies Symposium (PETS 2024)
issue: '2'
start: '211'
end: '234'
year: '2024'
month: July
address: Bristol, UK
publisher: PETS