Identifying Soft Biometric Features from a Combination of Keystroke and Mouse Dynamics

Earl, Sally; Campbell, James; Buckley, Oliver

doi:10.1007/978-3-030-79997-7_23

Cited by 5 publications

(2 citation statements)

References 16 publications

(14 reference statements)

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“…Therefore, it is important to predict this information based on similar patterns for the implementation of interesting applications. In addition, many studies [39]- [42], used these extra features like age and gender as extra features to improve the performance of the user authentication model. Therefore, it is also essential to predict this useful information as soft biometric traits.…”

Section: Motivation Of the Studymentioning

confidence: 99%

A Systematic Literature Review on Latest Keystroke Dynamics Based Models

et al. 2022

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The purpose of this study is to conduct a comprehensive evaluation and analysis of the most recent studies on the implications of keystroke dynamics (KD) patterns in user authentication, identification, and the determination of useful information. Another aim is to provide an extensive and up-to-date survey of the recent literature and potential research directions to understand the present state-of-the-art methodologies in this particular domain that are expected to be beneficial for the KD research community. From January 1st, 2017 to March 13th, 2022, the popular six electronic databases have been searched using a search criterion ("keystroke dynamics" OR "typing pattern") AND ("authentication" OR "verification" OR "identification"). With this criterion, a total of nine thousand three hundred forty-eight results, including duplicates, were produced. However, one thousand five hundred forty-seven articles have been chosen after removing duplicates and preliminary screening. Due to insufficient information, only one hundred twentyseven high-quality quantitative research articles have been included in the article selection process. We compared and summarised several factors with multiple tables to comprehend the various methodologies, experimental settings, and findings. In this study, we have identified six unique KD-based designs and presented the status of findings toward an effective solution in authentication, identification, and prediction. We have also discovered considerable heterogeneity across studies in each KD-based design for desktops and smartphones separately. Finally, this paper found a few open research challenges and provided some indications for a deeper understanding of the issues and further study.

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Section: Motivation Of the Studymentioning

confidence: 99%

A Systematic Literature Review on Latest Keystroke Dynamics Based Models

et al. 2022

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“…Here we treat keystroke and mouse dynamics as complementary non intrusive biometrics for active user authentication. It is shown by [Earl et al, (2021)] that a combination of keystroke and mouse features lend to better user authentication independent of the machine learning technique used to authenticate the user. Several works has been done using keystroke and mouse data.…”

Section: Machine Learning Based Active Authenticationmentioning

confidence: 99%

Active Behavioural Biometric Authentication Using Cat Swarm Optimization Variants With Deep Learning

Thomas¹,

K²

2022

INDJCSE

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Security issues have only been compounded by the advent of distributed networks and global internet availability. Combating these security issues depends on being able to correctly authenticate a valid user. This paper presents variants of our CRNM framework which is an efficient cat swarm optimized deep learning model to accurately authenticate a valid user through signature behavioral patterns and biometric information of the user. The behavioral patterns considered here are keystroke and mouse dynamics. Face recognition has been included as a means to decrease the false rejection rate of the system. The major contributions of this work include comparison of various cat optimization variants for active authentication, performance analysis of our model with different state of the art systems. The fitness functions tested include Rosenbrock, Rastrigin and Griewank while CSO variants studied are ADCSO, AICSO and PCSO. Results of our experiments indicate that the proposed authentication system is faster and more efficient than existing frameworks. We achieve accuracy 98.29%, FAR 0.01 and FRR 1.02.

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An Intelligent Approach for Fair Assessment of Online Laboratory Examinations in Laboratory Learning Systems Based on Student’s Mouse Interaction Behavior

et al. 2022

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The COVID-19 pandemic has made the world focus on providing effective and fair online learning systems. As a consequence, this paper proposed a new intelligent, fair assessment of online examinations for virtual and remotely controlled laboratory experiments running through Laboratory Learning Systems. The main idea is to provide students with an environment similar to being physically present in a Laboratory while conducting practical experiments and exams and detecting cheating with high accuracy at a minimal cost. Therefore, an intelligent assessment module is designed to detect cheating students by analyzing their mouse dynamics using Artificial Intelligence. The mouse interaction behavior method was chosen because it does not require any additional resources, such as a camera and eye tribe tracker, to detect cheating. Various AI algorithms, such as KNN, SVC, Random Forest, Logistic Regression, XGBoost, and LightGBM have been used to classify student mouse behavior to detect cheating, and many metrics are used to evaluate their performance. Moreover, experiments have been conducted on students answering online laboratory experimentations while cheating and when answering the exams honestly. Experimental results indicate that the LightGBM AI algorithm achieves the best cheat detection results up to an accuracy of 90%, precision of 88%, and degree of separation of 95%.

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Identifying Soft Biometric Features from a Combination of Keystroke and Mouse Dynamics

Cited by 5 publications

References 16 publications

A Systematic Literature Review on Latest Keystroke Dynamics Based Models

A Systematic Literature Review on Latest Keystroke Dynamics Based Models

Active Behavioural Biometric Authentication Using Cat Swarm Optimization Variants With Deep Learning

An Intelligent Approach for Fair Assessment of Online Laboratory Examinations in Laboratory Learning Systems Based on Student’s Mouse Interaction Behavior

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