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User Authentication Based on the Keystroke Dynamics using Multi-Layer Perceptron

Jetti, Lakshmi Bhargav (2021) User Authentication Based on the Keystroke Dynamics using Multi-Layer Perceptron. Masters thesis, Dublin, National College of Ireland.

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Abstract

In today’s age the use of computers has increased exponentially with a variety of online applications for public usage such as e-commerce, blogs, bank services etc. All of these existing online platforms require an authentication process to ensure the individuality of a genuine user. Despite of high-end encryption, it has become easy for intruders to enter the system and cause harm. Hence, arises the necessity of biometrics. One such example of biometrics is Keystroke dynamics which is known for its precise access control authentication process. The concept is known for its behavioral biometrics that makes use of typing patterns to analyze and gain insights of a user accessing the system. A total of 51 users are collected and asked to type a static password over a set of sessions repeated iteratively. Finally, the detection between a legit user and an intruder is being made based on the typing rhythms so obtained. The presented thesis directs its focus on the usage of deep learning model using the fundamentals of a Multilayer Perceptron to execute the working of keystroke dynamics.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Biometrics; multi-layer perceptron; keystroke dynamics; verification; user authentication
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Biometric Identification
Q Science > QA Mathematics > Computer software > Computer Security
T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions: School of Computing > Master of Science in Cyber Security
Depositing User: Clara Chan
Date Deposited: 19 Oct 2021 17:25
Last Modified: 19 Oct 2021 17:25
URI: https://norma.ncirl.ie/id/eprint/5116

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