Visible to the public Password authentication using Keystroke Biometrics

TitlePassword authentication using Keystroke Biometrics
Publication TypeConference Paper
Year of Publication2015
AuthorsD'Lima, N., Mittal, J.
Conference Name2015 International Conference on Communication, Information Computing Technology (ICCICT)
Date Publishedjan
ISBN Number978-1-4799-5522-0
Keywordsartificial neural network, Artificial neural networks, authentication, authorisation, biometrics (access control), Classification algorithms, Error analysis, error rates, Europe, Hardware, keystroke biometrics, Monitoring, neural nets, password, Password authentication, password security, Pattern matching, pubcrawl170115, robust security technique, security, Support vector machines, Text recognition, typing pattern matching, user behavior, user natural typing pattern, user verification mechanism
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.

URLhttp://ieeexplore.ieee.org/document/7045681/
DOI10.1109/ICCICT.2015.7045681
Citation Keydlima_password_2015