Advertisement

Privacy-Aware Device Identifier through a Trusted Web Service

  • Marcelo da Cruz Pinto
  • Ricardo Morin
  • Maria Emilia Torino
  • Danny Varner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6470)

Abstract

Device identifiers can be used to enhance authentication mechanisms for conducting online business. However, personal computers (PC) today are not equipped with standardized, privacy-aware hardware-based device identifiers for general use. This paper describes the implementation of privacy-aware device identifiers using the capabilities of the Trusted Platform Module (TPM) and extending the trust boundary of the device using a Web Service. It also describes a case study based on a device reputation service.

Keywords

device identifiers identity privacy protected execution reputation systems TPM Web Services 

References

  1. 1.
    Trusted computing group software stack (2010), http://www.trustedcomputinggroup.org/developers/software_stack
  2. 2.
  3. 3.
  4. 4.
    Balfe, S., Lakhani, A.D., Paterson, K.G.: Trusted computing: Providing security for peer-to-peer networks. In: IEEE International Conference on Peer-to-Peer Computing, pp. 117–124 (2005)Google Scholar
  5. 5.
  6. 6.
    McFadden, T.: Tpm matrix (2006), http://www.tonymcfadden.net/tpmvendors_arc.html
  7. 7.
    Ahamad, M., et al: Emerging cyber threats report for 2009 (2008), http://www.gtisc.gatech.edu/pdf/CyberThreatsReport2009.pdf
  8. 8.
    Needham, R.M., Schroeder, M.D.: Using encryption for authentication in large networks of computers. Commun. ACM 21(12), 993–999 (1978)CrossRefzbMATHGoogle Scholar
  9. 9.
    O’Gorman, L.: Comparing passwords, tokens, and biometrics for user authentication. Proceedings of the IEEE 91(12), 2021–2040 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marcelo da Cruz Pinto
    • 1
  • Ricardo Morin
    • 1
  • Maria Emilia Torino
    • 1
  • Danny Varner
    • 1
  1. 1.Intel CorporationUSA

Personalised recommendations