Name
Abstract | ||
|---|---|---|
Biometric security systems enable more secure authentication methods to access a computer system's resources. This paper presents a biometric security system based on keystroke dynamics that enable hardening or strengthening the password verification process by comparing the captured keystroke dynamics information with the user's templates stored in a template database. The system uses the statistical information about keystroke latencies of users as a measure to differentiate different users. It uses a classifier that resembles a neural network as the structure. |
Year | Venue | Keywords |
|---|---|---|
2007 | Artificial Intelligence and Applications | enhanced password authentication,secure authentication method,keystroke typing characteristic,computer system,neural network,different user,password verification process,statistical information,biometric security system,keystroke dynamics information,keystroke dynamic,keystroke latency,computer security,password authentication,keystroke dynamics,biometrics |
Field | DocType | Citations |
Computer security,Computer science,Keystroke dynamics,Keystroke logging,Human–computer interaction,Typing,Password,Biometrics,Password authentication protocol,Artificial neural network,Classifier (linguistics) | Conference | 3 |
PageRank | References | Authors |
0.45 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ozlem Guven | 1 | 3 | 0.45 |
| Selim Akyokus | 2 | 17 | 1.92 |
| Mitat Uysal | 3 | 70 | 4.54 |
| Aykut Guven | 4 | 12 | 1.11 |