Improving static audio keystroke analysis by score fusion of acoustic and timing data

Pleva, Matúš; Bours, Patrick; Ondáš, Stanislav; Juhár, Jozef

doi:10.1007/s11042-017-4571-7

Cited by 13 publications

(6 citation statements)

References 17 publications

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“…This indicates that a change in hardware would result in an increased variation in the samples. In another longitudinal study combining key timings and acoustic timings, the second session was identified as best [33]; however, their study included 50 participants typing the same phrase (‘password’) 25 times in a session, repeated 4 times. The absence of changing the typed password means direct comparisons with our work cannot be made.…”

Section: Resultsmentioning

confidence: 99%

An empirical analysis of keystroke dynamics in passwords: A longitudinal study

et al. 2022

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The use of keystroke timings as a behavioural biometric in fixed-text authentication mechanisms has been extensively studied. Previous research has investigated in isolation the effect of password length, character substitution, and participant repetition. These studies have used publicly available datasets, containing a small number of passwords with timings acquired from different experiments. Multiple experiments have also used the participant's first and last name as the password; however, this is not realistic of a password system. Not only is the user's name considered a weak password, but their familiarity with typing the phrase minimises variation in acquired samples as they become more familiar with the new password. Furthermore, no study has considered the combined impact of length, substitution, and repetition using the same participant pool. This is explored in this work, where the authors collected timings for 65 participants, when typing 40 passwords with varying characteristics, 4 times per week for 8 weeks. A total of 81,920 timing samples were processed using an instance-based distance and threshold matching approach. Results of this study provide empirical insight into how a password policy should be created to maximise the accuracy of the biometric system when considering substitution type and longitudinal effects.

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Section: Resultsmentioning

confidence: 99%

An empirical analysis of keystroke dynamics in passwords: A longitudinal study

et al. 2022

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“…Other applications, already under development, are training of civil engineering personnel, safety training and visualization of data from physical experiments in virtual environments. Such applications can also be extended by undergoing developments regarding authentication utilizing keyboard dynamics [41], additional EMG sensing and face recognition, together with emotion recognition [42] and EEG sensing. The experimental setup, introduced in this article, will be reused for other evaluations.…”

Section: Discussionmentioning

confidence: 99%

Experimental Performance Evaluation of Enhanced User Interaction Components for Web-Based Collaborative Extended Reality

et al. 2021

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COVID-19-related quarantine measures resulted in a significant increase of interest in online collaboration tools. This includes virtual reality (VR) or, in more general term, extended reality (XR) solutions. Shared XR allows for activities such as presentations, training of personnel or therapy to take place in a virtual space instead of a real one. To make online XR as accessible as possible, a significant effort has been put into the development of solutions that can run directly in web browsers. One of the most recognized solutions is the A-Frame software framework, created by Mozilla VR team and supporting most of the contemporary XR hardware. In addition, an extension called Networked-Aframe allows multiple users to share virtual environments, created using A-Frame, in real time. In this article, we introduce and experimentally evaluate three components that extend the functionality of A-Frame and Networked-Aframe. The first one extends Networked-Aframe with the ability to monitor and control users in a shared virtual scene. The second one implements six degrees of freedom motion tracking for smartphone-based VR headsets. The third one brings hand gesture support to the Microsoft HoloLens holographic computer. The evaluation was performed in a dedicated local network environment with 5, 10, 15 and 20 client computers. Each computer represented one user in a shared virtual scene. Since the experiments were carried out with and without the introduced components, the results presented here can also be regarded as a performance evaluation of A-Frame and Networked-Aframe themselves.

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“…The results presented in this paper using a fusion system for automatic facial emotion recognition are promising. In the future, the audio features and speaker emotion detection models [43] will also be tested and fused [44] with the frame-level results.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Facial Expression Emotion Detection for Real-Time Embedded Systems

et al. 2018

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Abstract:Recently, real-time facial expression recognition has attracted more and more research. In this study, an automatic facial expression real-time system was built and tested. Firstly, the system and model were designed and tested on a MATLAB environment followed by a MATLAB Simulink environment that is capable of recognizing continuous facial expressions in real-time with a rate of 1 frame per second and that is implemented on a desktop PC. They have been evaluated in a public dataset, and the experimental results were promising. The dataset and labels used in this study were made from videos, which were recorded twice from five participants while watching a video. Secondly, in order to implement in real-time at a faster frame rate, the facial expression recognition system was built on the field-programmable gate array (FPGA). The camera sensor used in this work was a Digilent VmodCAM -stereo camera module. The model was built on the Atlys TM Spartan-6 FPGA development board. It can continuously perform emotional state recognition in real-time at a frame rate of 30. A graphical user interface was designed to display the participant's video in real-time and two-dimensional predict labels of the emotion at the same time.

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Improving static audio keystroke analysis by score fusion of acoustic and timing data

Cited by 13 publications

References 17 publications

An empirical analysis of keystroke dynamics in passwords: A longitudinal study

An empirical analysis of keystroke dynamics in passwords: A longitudinal study

Experimental Performance Evaluation of Enhanced User Interaction Components for Web-Based Collaborative Extended Reality

Facial Expression Emotion Detection for Real-Time Embedded Systems

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