Capturing Cognitive Processing Time for Active Authentication
J. Morris Chang · 2014
Abstract : This report presents an authentication system that applies machine learning techniques to observe a user s cognitive typing rhythm. A new feature called cognitive typing rhythm (CTR) is used to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous authentication. Its effectiveness has been verified through a campus-wide experiment at Iowa State University. Furthermore, a live demo was performed twice to demonstrate the effectiveness of our system.