From data privacy to location privacy: models and algorithms

  • Authors:

  • Ling Liu

  • Affiliations:

  • Georgia Institute of Technology

  • Venue:
  • VLDB '07 Proceedings of the 33rd international conference on Very large data bases
  • Year:
  • 2007

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Abstract

This tutorial presents the definition, the models and the techniques of location privacy from the data privacy perspective. By reviewing and revising the state of art research in data privacy area, the presenter describes the essential concepts, the alternative models, and the suite of techniques for providing location privacy in mobile and ubiquitous data management systems. The tutorial consists of two main components. First, we will introduce location privacy threats and give an overview of the state of art research in data privacy and analyze the applicability of the existing data privacy techniques to location privacy problems. Second, we will present the various location privacy models and techniques effective in either the privacy policy based framework or the location anonymization based framework. The discussion will address a number of important issues in both data privacy and location privacy research, including the location utility and location privacy trade-offs, the need for a careful combination of policy-based location privacy mechanisms and location anonymization based privacy schemes, as well as the set of safeguards for secure transmission, use and storage of location information, reducing the risks of unauthorized disclosure of location information. The tutorial is designed to be self-contained, and gives the essential background for anyone interested in learning about the concept and models of location privacy, and the principles and techniques for design and development of a secure and customizable architecture for privacy-preserving mobile data management in mobile and pervasive information systems. This tutorial is accessible to data management administrators, mobile location based service developers, and graduate students and researchers who are interested in data management in mobile information syhhhstems, pervasive computing, and data privacy.