User Authentication via Keystroke Dynamics: An Artificial Immune System Based Approach

Keystroke dynamics is a behavioral biometric that is based on how a user enters their login details. In this study, a set of eight attributes were extracted during the course of entering login details. This collection of attributes was used to form a reference signature (a biometric identification record) for subsequent authentication requests. The algorithm for the authentication process entails the deployment of an artificial immune based approach. The approach uses self-reactivity to discriminate self from non-self from the enrollment data. During the classification task, the system relies on deploying a pool of non-self reactive antibodies to perform a very general classification task. The results of this study indicate that the error rate is less than 5% in many cases.