Keystroke Dynamics Authentication Using Neural Network Approaches

9Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Securing the sensitive data and computer systems by allowing ease access to authenticated users and withstanding the attacks of imposters is one of the major challenges in the field of computer security. Traditionally, ID and password schemes are most widely used for controlling the access to computer systems. But, this scheme has many flaws such as Password sharing, Shoulder surfing, Brute force attack, Dictionary attack, Guessing, Phishing and many more. Biometrics technologies provide more reliable and efficient means of authentication and verification. Keystroke Dynamics is one of the famous biometric technologies, which will try to identify the authenticity of a user when the user is working with a keyboard. In this paper, neural network approaches with three different passwords namely weak, medium and strong passwords are taken into consideration and accuracy obtained is compared. © Springer-Verlag Berlin Heidelberg 2010.

Cite

CITATION STYLE

APA

Shanmugapriya, V., & Padmavathi, G. (2010). Keystroke Dynamics Authentication Using Neural Network Approaches. In Communications in Computer and Information Science (Vol. 101, pp. 686–690). https://doi.org/10.1007/978-3-642-15766-0_121

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free