Applying Computational Intelligence Techniques for Personal Authentication using Keystroke Dynamics

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dc.categoryJournal Article
dc.contributor.authorPadmavathi, G
dc.date.accessioned2017-03-28T22:30:36Z
dc.date.available2017-03-28T22:30:36Z
dc.date.issued2013
dc.departmentComputer Scienceen_US
dc.description.abstractABSTRACTUsername with password is the commonly used authentication mechanism for securing huge data transactions being carried out every day via Internet. Most of the text based authentication methods are vulnerable to many attacks as they 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 behavioral biometric technologies, which identifies the authenticity of a user when the user is working via a keyboard. The paper uses computational intelligence techniques such as Genetic algorithm. Ant Colony Optimization and Particle Swarm Optimization for feature subset selection and Back propagation Neural Network for classification. From the results, it is observed that ACO wrapped with BPN outperforms the other methods.en_US
dc.identifier.urihttps://ir.avinuty.ac.in/handle/avu/2243
dc.langEnglishen_US
dc.publisher.nameInternational Journal of Advanced Networking And Applicationen_US
dc.publisher.typeInternationalen_US
dc.titleApplying Computational Intelligence Techniques for Personal Authentication using Keystroke Dynamicsen_US
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