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Secure OpenID Authentication Model by Using Trusted Computing

Author

Listed:
  • E. Ghazizadeh
  • Z. S. Shams Dolatabadi
  • R. Khaleghparast
  • M. Zamani
  • A. A. Manaf
  • M. S. Abdullah

Abstract

The growth of Internet online services has been very quick in recent years. Each online service requires Internet users to create a new account to use the service. The problem can be seen when each user usually needs more than one service and, consequently, has numerous accounts. These numerous accounts have to be managed in a secure and simple way to be protected against identity theft. Single sign‐on (SSO) and OpenID have been used to decrease the complexity of managing numerous accounts required in the Internet identity environment. Trusted Platform Module (TPM) and Trust Multitenancy are great trusted computing‐based technologies to solve security concerns in the Internet identity environment. Since trust is one of the pillars of security in the cloud, this paper analyzes the existing cloud identity techniques in order to investigate their strengths and weaknesses. This paper proposes a model in which One Time Password (OTP), TPM, and OpenID are used to provide a solution against phishing as a common identity theft in cloud environment.

Suggested Citation

  • E. Ghazizadeh & Z. S. Shams Dolatabadi & R. Khaleghparast & M. Zamani & A. A. Manaf & M. S. Abdullah, 2014. "Secure OpenID Authentication Model by Using Trusted Computing," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnlaaa:v:2014:y:2014:i:1:n:561487
    DOI: 10.1155/2014/561487
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    References listed on IDEAS

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    1. Shen Yin & Guang Wang & Xu Yang, 2014. "Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(7), pages 1375-1382, July.
    2. Baocheng Huang & Guang Yu, 2014. "Research and Application of Personalized Modeling Based on Individual Interest in Mining," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-8, August.
    3. Ehsan Amiri & Hassan Keshavarz & Mojtaba Alizadeh & Mazdak Zamani & Touraj Khodadadi, 2014. "Energy Efficient Routing in Wireless Sensor Networks Based on Fuzzy Ant Colony Optimization," International Journal of Distributed Sensor Networks, , vol. 10(7), pages 768936-7689, July.
    4. Baocheng Huang & Guang Yu, 2014. "Research and Application of Personalized Modeling Based on Individual Interest in Mining," Abstract and Applied Analysis, John Wiley & Sons, vol. 2014(1).
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