Continuous Authentication Using Behavioural Biometrics: A Step Towards Enhancing Authentication for Distance Learning in Jamaica

2021 ◽  
Author(s):  
Kenique Rodney ◽  
Shaneekea Ricketts ◽  
Leighton Mitchell ◽  
Sean Thorpe
Keyword(s):  
Distance Learning ◽  
Continuous Authentication ◽  
Behavioural Biometrics

Importance of a Versatile Logging Tool for Behavioural Biometrics and Continuous Authentication Research

2017 ◽  
pp. 282-305
Author(s):  
Soumik Mondal ◽  
Patrick Bours ◽  
Lasse Johansen ◽  
Robin Stenvi ◽  
Magnus Øverbø
Keyword(s):  
Operating System ◽  
Intrusion Detection ◽  
High Precision ◽  
Sensitive Data ◽  
Log Data ◽  
Design And Implementation ◽  
Continuous Authentication ◽  
Behavioural Biometrics ◽  
Logging Tool

We present the design and implementation of a Windows operating system based logging tool, which can capture the keystroke, mouse, software interaction and hardware usage simultaneously and continuously. Log data can be stored locally or transmitted in a secure manner to a server. Filter drivers are used to log with high precision. Privacy of the users and confidentiality of sensitive data have been taken into account throughout the development of the tool. Our behaviour logging software is mainly designed for behavioural biometrics research, but its scope could also be beneficial to proactive forensics and intrusion detection. We show the validity of the tool in a study of keyboard and mouse data uses for continuous authentication.

scholarly journals Euler Movement Firefly Algorithm and Fuzzy Kernel Support Vector Machine Classifier for Keystroke Authentication

2019 ◽  
Vol 8 (11) ◽  
pp. 2267-2274
Keyword(s):  
Support Vector Machine ◽  
Firefly Algorithm ◽  
User Authentication ◽  
Modern Method ◽  
User Profiling ◽  
Support Vector ◽  
Free Text ◽  
Continuous Authentication ◽  
Kernel Support Vector Machine ◽  
Behavioural Biometrics

User authentication can be successfully employed using keyboard typing patterns which is a form of behavioural biometrics. This modern method is highly analyzed for static authentication which refers to typing of fixed texts like ‘password’ and ‘pin numbers’. Most of the methods with respect to keystroke dynamics are restricted to the study of user’s activity involving fixed text. The formulated work concentrates on the investigation of the log of the user activity focused on the keyboard usage within the computer system through free text which refers to typing of texts throughout the login session. The Buffalo dataset is used in User Profiling Similarity Measurement (UPSM) stage and to recognize the time slice of the users, Euler Movement Firefly Algorithm (EMFA) is utilized. The typing behaviour is formulated in the form of time series in User Profiling Continuous Keystroke Authentication (UPCKA). Moreover the progression is made to user’s Continuous Authentication so as to predict unauthorized users with the consideration of the classifier called Novel Fuzzy Kernel Support Vector Machine (NFKSVM). The experimental results provide the enhanced performance by utilizing the formulated UPCKA in correlation with the NFKSVM classifier when compared with SVM and Iterative Keystroke Continuous Authentication (IKCA) techniques

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