Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

DOI

10.2991/ijcis.2011.4.4.2How to use a DOI?

Keywords

authentication, fuzzy logic, neural networks, identity attributes, metrics model, information fusion.

Abstract

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.

Copyright

© 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/).

Download article (PDF)

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  -