Privacy Support for the Total Learning Architecture Volume 2: Modeling Factors

Abstract

The purpose of this document is to make recommendations for implementing User-Tailored Privacy (UTP) into Total Learning Architecture (TLA)-based systems and to inform ADL and other TLA performers about the Modeling Factors that need to be considered in the context of this implementation. The set of recommendations put forth in this document will allow ADL and other TLA performers to build a user-tailored privacy decision-support system that supports users in making better privacy decisions.

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Document Details

Document Type
Technical Report
Publication Date
Jul 31, 2018
Accession Number
AD1064608

Entities

People

  • Alexander D. Johnson
  • Bart P. Knijnenburg
  • David Cherry
  • Erin Ash
  • Moses Namara
  • Reza G. Anaraky
  • Yang He

Organizations

  • Clemson University

Tags

Communities of Interest

  • Autonomy
  • Biomedical
  • Cyber
  • Human Systems

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognitive Systems Engineering
  • Computational Science
  • Computers
  • Cybersecurity
  • Data Mining
  • Distance Learning
  • Electronic Commerce
  • Electronic Mail
  • Human Behavior
  • Human-Computer Interaction
  • Information Exchange
  • Information Processing
  • Information Science
  • Information Systems
  • Internet
  • Machine Learning
  • Mobile Application Software
  • Multiagent Systems
  • Network Science
  • Psychology
  • Social Media
  • Social Networking Services
  • Social Networks

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Life Cycle Cost Analysis