The Impact of Expressiveness on the Effectiveness of Privacy Mechanisms for Location Sharing

Abstract

A recent trend on the Web is a demand for higher levels of expressiveness in the mechanisms that mediate interactions such as the allocation of resources, matching of peers, or elicitation of opinions. In this paper, we demonstrate the need for greater expressiveness in privacy mechanisms, which control the conditions under which private information is shared on the Web. We begin by adapting our recent theoretical framework for characterizing expressiveness to this domain. By leveraging prior results, we are able to prove that any increase in allowed expressiveness for privacy mechanisms leads to a strict improvement in their efficiency (i.e., the ability of individuals to share information without violating their privacy constraints). We validate these theoretical results with a week-long human subject experiment, where we tracked the locations of 30 subjects. Each day we collected their stated ground truth privacy preferences regarding sharing their locations with different groups of people. Our results confirm that 1) most subjects had relatively complex privacy preferences, and 2) that privacy mechanisms with higher levels of expressiveness are significantly more efficient in this domain.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA507046

Entities

People

  • Janice Tsai
  • Lorrie F. Cranor
  • Michael Benisch
  • Norman Sadeh
  • Patrick G. Kelley
  • Paul H. Drielsma
  • Tuomas Sandholm

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Business Administration
  • Commerce
  • Communities
  • Computer Science
  • Computers
  • Efficiency
  • Energy Consumption
  • Grids
  • Intervals
  • Mobile Phones
  • Probability
  • Probability Distributions
  • Social Media
  • User Interface
  • Web Applications
  • Websites
  • Wireless Computer Networks

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience