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DOI: 10.14569/IJARAI.2014.031005
PDF

Modelling and Simulation of a Biometric Identity-Based Cryptography

Author 1: Dania Aljeaid
Author 2: Xiaoqi Ma
Author 3: Caroline Langensiepen

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 3 Issue 10, 2014.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Government information is a vital asset that must be kept in a trusted environment and efficiently managed by authorised parties. Even though e-Government provides a number of advantages, it also introduces a range of new security risks. Sharing confidential and top-secret information in a secure manner among government sectors tends to be the main element that government agencies look for. Thus, developing an effective methodology is essential and it is a key factor for e-Government success. The proposed e-Government scheme in this paper is a combination of identity-based encryption and biometric technology. This new scheme can effectively improve the security in authentication systems, which provides a reliable identity with a high degree of assurance. This paper also demonstrates the feasibility of using finite-state machines as a formal method to analyse the proposed protocols. Finally we showed how Petri Nets could be used to simulate the communication patterns between the server and client as well as to validate the protocol functionality.

Keywords: e-Government; identity-based cryptosystem; biometrics; mutual authentication; finite-state machine; Petri net.

Dania Aljeaid, Xiaoqi Ma and Caroline Langensiepen, “Modelling and Simulation of a Biometric Identity-Based Cryptography” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 3(10), 2014. http://dx.doi.org/10.14569/IJARAI.2014.031005

@article{Aljeaid2014,
title = {Modelling and Simulation of a Biometric Identity-Based Cryptography},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2014.031005},
url = {http://dx.doi.org/10.14569/IJARAI.2014.031005},
year = {2014},
publisher = {The Science and Information Organization},
volume = {3},
number = {10},
author = {Dania Aljeaid and Xiaoqi Ma and Caroline Langensiepen}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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