Framework for security and privacy in automotive telematics

  • Authors:
  • Sastry Duri;Marco Gruteser;Xuan Liu;Paul Moskowitz;Ronald Perez;Moninder Singh;Jung-Mu Tang

  • Affiliations:
  • IBM Thomas J. Watson Research Center, Hawthorne, New York;IBM Thomas J. Watson Research Center, Hawthorne, New York;IBM Thomas J. Watson Research Center, Hawthorne, New York;IBM Thomas J. Watson Research Center, Hawthorne, New York;IBM Thomas J. Watson Research Center, Hawthorne, New York;IBM Thomas J. Watson Research Center, Hawthorne, New York;IBM Thomas J. Watson Research Center, Hawthorne, New York

  • Venue:
  • WMC '02 Proceedings of the 2nd international workshop on Mobile commerce
  • Year:
  • 2002

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Abstract

Automotive telematics may be defined as the information-intensive applications that are being enabled for vehicles by a combination of telecommunications and computing technology. Telematics by its nature requires the capture of sensor data, storage and exchange of data to obtain remote services. In order for automotive telematics to grow to its full potential, telematics data must be protected. Data protection must include privacy and security for end-users, service providers and application providers. In this paper, we propose a new framework for data protection that is built on the foundation of privacy and security technologies. The privacy technology enables users and service providers to define flexible data model and policy models. The security technology provides traditional capabilities such as encryption, authentication, non-repudiation. In addition, it provides secure environments for protected execution, which is essential to limiting data access to specific purposes.