Title :
Password authentication using Keystroke Biometrics
Author :
D´Lima, Nathan ; Mittal, Jayashri
Author_Institution :
Comput. Dept., St. Francis Inst. of Technol., Mumbai, India
Abstract :
The majority of applications use a prompt for a username and password. Passwords are recommended to be unique, long, complex, alphanumeric and non-repetitive. These reasons that make passwords secure may prove to be a point of weakness. The complexity of the password provides a challenge for a user and they may choose to record it. This compromises the security of the password and takes away its advantage. An alternate method of security is Keystroke Biometrics. This approach uses the natural typing pattern of a user for authentication. This paper proposes a new method for reducing error rates and creating a robust technique. The new method makes use of multiple sensors to obtain information about a user. An artificial neural network is used to model a user´s behavior as well as for retraining the system. An alternate user verification mechanism is used in case a user is unable to match their typing pattern.
Keywords :
authorisation; biometrics (access control); neural nets; pattern matching; artificial neural network; error rates; keystroke biometrics; password authentication; password security; robust security technique; typing pattern matching; user behavior; user natural typing pattern; user verification mechanism; Classification algorithms; Error analysis; Europe; Hardware; Monitoring; Support vector machines; Text recognition; Artificial Neural Networks; Authentication; Keystroke Biometrics; Password; Security;
Conference_Titel :
Communication, Information & Computing Technology (ICCICT), 2015 International Conference on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4799-5521-3
DOI :
10.1109/ICCICT.2015.7045681
