Conference & Journal Paper
Understanding and Capturing People's Privacy Policies in a People Finder Application
Norman Sadeh, Jason I. Hong, Lorrie Faith Cranor, Ian Fette, Patrick Gage Kelley, Madhu Prabaker, Jinghai Rao
Personal and Ubiquitous Computing, 13(6), August 2009
August 2009
Abstract
A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends, family, and colleagues). The objective of our work has been to better understand people's attitudes and behaviors towards privacy as they interact with such an application, and to explore technologies that empower users to more effectively and efficiently specify their privacy preferences (or "policies"). These technologies include user interfaces for specifying rules and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present evaluations of these technologies in the context of one laboratory study and three field studies.
- location sharing
- privacy
- gps
- privacy controls
Cite this paper
@inproceedings{sadeh2009understanding,
title = {Understanding and Capturing People's Privacy Policies in a People Finder Application},
author = {Sadeh, Norman and Hong, Jason I. and Cranor, Lorrie Faith and Fette, Ian and Kelley, Patrick Gage and Prabaker, Madhu and Rao, Jinghai},
year = {2009},
booktitle = {Personal and Ubiquitous Computing, 13(6), August 2009},
url = {https://pgk.io/papers/2009-understanding-and-capturing-people-s-privacy-policies-in-a/},
}