Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System
- 10.2991/ijcis.2011.4.4.2How to use a DOI?
- authentication, fuzzy logic, neural networks, identity attributes, metrics model, information fusion.
The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.
- © 2011, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Jackson Phiri AU - Tie-Jun Zhao AU - Cong Hui Zhu AU - Jameson Mbale PY - 2011 DA - 2011/06/01 TI - Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System JO - International Journal of Computational Intelligence Systems SP - 420 EP - 430 VL - 4 IS - 4 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.2011.4.4.2 DO - 10.2991/ijcis.2011.4.4.2 ID - Phiri2011 ER -