| Type of Material: | Thesis |
| Title: | An Efficient Framework for Continuous Non Intrusive User Authentication Using Deep Learning |
| Researcher: | Thomas, Princy Ann |
| Guide: | Preetha Mathew, K |
| Department: | Cochin University College of Engineering Kuttanadu |
| Publisher: | Cochin University of Science & Technology, Cochin |
| Place: | Cochin |
| Year: | 2023 |
| Language: | English |
| Subject: | Cat Swarm Optimization | Computer Science | Continuous User Authentication | Engineering and Technology | Feature Extraction and Selection. | Keystroke Dynamics | Mouse Dynamics | Recurrent Neural Network | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Cochin University College of Engineering Kuttanadu, Cochin University of Science & Technology, Cochin, Cochin |
| Fulltext: | Shodhganga |
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| 003 | IN-AhILN | |
| 005 | 2024-10-09 10:56:08 | |
| 008 | __ | 241009t2023||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_456296 |
| 040 | __ | |aCUST_682022|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aThomas, Princy Ann|eResearcher |
| 110 | __ | |aCochin University College of Engineering Kuttanadu|bCochin University of Science & Technology, Cochin|dCochin|ein|0U-0253 |
| 245 | __ | |aAn Efficient Framework for Continuous Non Intrusive User Authentication Using Deep Learning |
| 260 | __ | |aCochin|bCochin University of Science & Technology, Cochin|c2023 |
| 300 | __ | |axviii,215|dDVD |
| 502 | __ | |bPhD|cCochin University College of Engineering Kuttanadu, Cochin University of Science & Technology, Cochin, Cochin |
| 518 | __ | |d2024|oDate of Award |
| 518 | __ | |d2018|oDate of Registration |
| 520 | __ | |aAuthentication is the first step in keeping personal information confidential in the digital world. The user authentication processes verify the legitimacy of users by methods like login credential verification, biometrics, voice recognition, digital signature and so on. Traditionally, one-time login based credential verification has many limitations and is prone to cyber attacks. Furthermore, single authentication at the start of a session leaves a user open to intrusion if the user leaves the station unattended. Several new approaches are proposed to enhance the user authentication framework. They are found to be ineffective and inconsistent. In recent years, continuous user authentication (CUA) based on mouse and keystroke dynamics have been studied extensively. They have inherent advantages like non intrusiveness, non requirement of additional hardware and improved security. A commercially deployable CUA system for multiple application areas is yet to be seen because fast authentication and high perform |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aCat Swarm Optimization |
| 653 | __ | |aComputer Science |
| 653 | __ | |aContinuous User Authentication |
| 653 | __ | |aEngineering and Technology |
| 653 | __ | |aFeature Extraction and Selection. |
| 653 | __ | |aKeystroke Dynamics |
| 653 | __ | |aMouse Dynamics |
| 653 | __ | |aRecurrent Neural Network |
| 700 | __ | |eGuide|aPreetha Mathew, K |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/551691|yShodhganga |
| 905 | __ | |afromsg |
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