A static authentication framework based on mouse gesture dynamics
| dc.contributor.author | Sayed, Bassam | |
| dc.contributor.supervisor | Traore, Issa | |
| dc.date.accessioned | 2010-06-02T18:06:49Z | |
| dc.date.available | 2010-06-02T18:06:49Z | |
| dc.date.copyright | 2009 | en |
| dc.date.issued | 2010-06-02T18:06:49Z | |
| dc.degree.department | Department of Electrical and Computer Engineering | |
| dc.degree.level | Master of Applied Science M.A.Sc. | en |
| dc.description.abstract | Mouse dynamics biometrics is a behavioural biometrics technology which consists of the movement characteristics of the mouse input device when a computer user is interacting with a graphical user interface. However, existing studies on mouse dynamics analysis have targeted primainely continuous authentication or user reauthentication for which promising results have been achieved. Static authentication using mouse dynamics appear to face some challenges because of the limited amount of data that could reasonably be captured during such process. We present, in this thesis, a new mouse dynamics analysis framework that uses mouse gesture dynamics for static authentication. The captured gestures are analyzed using LVQ neural network classifier. We conducted an experimental evaluation of our framework involving 41 users, achieving FAR = 1.55% and FRR = 2% when four gestures are combined. | en |
| dc.identifier.uri | http://hdl.handle.net/1828/2833 | |
| dc.language | English | eng |
| dc.language.iso | en | en |
| dc.rights | Available to the World Wide Web | en |
| dc.subject | Mice (Computers) | en |
| dc.subject | Authentication | en |
| dc.subject.lcsh | UVic Subject Index::Sciences and Engineering::Applied Sciences::Computer science | en |
| dc.title | A static authentication framework based on mouse gesture dynamics | en |
| dc.type | Thesis | en |