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Continuous Authentication for Mouse Gesture Recognition using Hidden Markov Model
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vanishree, C. |
| Copyright Year | 2017 |
| Abstract | The mouse dynamics biometric is a behavioral biometric technology that extracts and analyzes the movement characteristics of the mouse input device when a computer user interacts with a graphical user interface for identification purposes. The existing mouse dynamics analyzes has continuous authentication or reauthentication for which exact results have been achieved. Static authentication using mouse gesture dynamics faces some challenges because of the limited amount of data that has captured. Authentication is the process of determining whether someone or something is, in fact, who or what it claim to be. A new category of biometrics that is gaining popularity is behaviometrics, where analysis focuses on the user s behavior while he interacts with computing systems for identification purposes. In this paper, a new mouse dynamics analysis framework uses mouse gesture dynamics for static authentication. The captured gestures are analyzed using a Hidden Markov Model. This results in improvement of both the accuracy and validation compared to the existing mouse dynamics approaches. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.iject.org/vol8/issue4/1-chinmayee-k-s.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
