Personalized Privacy Assistants for Big Data and the Internet of Things

Abstract

The Personalized Privacy Assistants for Big Data and the Internet of Things (IoT) project developed, demonstrated and evaluated novel techniques that empower end-users to effectively evaluate privacy policies and configure privacy settings in realistic mobile and IoT environments. This included addressing privacy challenges associated with Big Data and developing a privacy infrastructure that enables the automated discovery of IoT resources and their privacy practices. It also included work on privacy risks in Big Data machine learning pipelines. This report summarizes the research performed over the course of the project and major results.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2021
Accession Number
AD1140163

Entities

People

  • Alessandro Acquisti
  • Anupam Datta
  • Lorrie Crano
  • Lujo Bauer
  • Matt Fredrikson
  • Matthew Tschantz
  • Norman Sadeh

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Cyber
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computers
  • Governments
  • Information Science
  • Information Systems
  • Law
  • Machine Learning
  • Natural Language Processing
  • Network Science
  • Smartphones
  • Supervised Machine Learning
  • Web Browsers

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Distributed Systems and Data Platform Development

Technology Areas

  • 5G
  • 5G - Internet of Things
  • AI & ML