Applying Computational Intelligence Techniques for Personal Authentication using Keystroke Dynamics
| dc.category | Journal Article | |
| dc.contributor.author | Shanmugapriya, D | |
| dc.date.accessioned | 2017-04-18T19:26:49Z | |
| dc.date.available | 2017-04-18T19:26:49Z | |
| dc.date.issued | 2013 | |
| dc.department | Information Technology | en_US |
| dc.description.abstract | ABSTRACTUsername -with password is the commonly used authentication mechanism for securing huge data transactions being carried out everj' day via Internet. Most of the text based authentication methods arc vulnerable to manv attacks as thev depend on text and can be strengthened more by combining password with key typing manner of the user. Keystroke Dynamics is one of the inexpensive and strong beliavioral biometric technologies, which identifies the authenticity of a user when the u.ser is working via a keyboard. Tlic paper uses computational intelligence tcehnkiues such as Genetic algorithm. Ant Colony Optimization and Particle Swarm Optimization for feature sub.set selection and back propagation Neural Nebvork for classification. From the results, it is observed that ACO wrapped with BPN outperforms the other methods. | en_US |
| dc.identifier.uri | https://ir.avinuty.ac.in/handle/avu/3239 | |
| dc.lang | English | en_US |
| dc.publisher.name | International Journal of Advanced Networking And Application | en_US |
| dc.publisher.type | International | en_US |
| dc.title | Applying Computational Intelligence Techniques for Personal Authentication using Keystroke Dynamics | en_US |
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