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Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic
The Global Novel Coronavirus Disease-2019 (COVID-19) pandemic has forced social distancing norms that have been followed worldwide. Thus, traditional biometric-based attendance marking systems are replaced with contactless attendance marking schemes. However, there are limitations of manufacturing c...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886322/ https://www.ncbi.nlm.nih.gov/pubmed/36743795 http://dx.doi.org/10.1016/j.procs.2023.01.129 |
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author | Saraswat, Deepti Bhattacharya, Pronaya Shah, Tirth Satani, Rushi Tanwar, Sudeep |
author_facet | Saraswat, Deepti Bhattacharya, Pronaya Shah, Tirth Satani, Rushi Tanwar, Sudeep |
author_sort | Saraswat, Deepti |
collection | PubMed |
description | The Global Novel Coronavirus Disease-2019 (COVID-19) pandemic has forced social distancing norms that have been followed worldwide. Thus, traditional biometric-based attendance marking systems are replaced with contactless attendance marking schemes. However, there are limitations of manufacturing cost, spoofing attacks, and security vulnerabilities. Thus, the paper proposes a contactless camera-based attendance system with the equipped functionalities of anti-spoofing. The proposed scheme can detect liveliness, so fake attendance marking is eliminated. The proposed scheme is also scalable and cost-effective, with generic solutions adaptable to schools, colleges, or other places where attendance is required. The system also eliminates the limitation of one-entry by multiple face-marking systems that allow simultaneous attendance marking. In performance analysis, parameters like image precision, storage cost, retrieval latency, and analysis of the anti-spoofing module is presented against existing schemes. An accuracy of 95.85% is reported for the model, with a significant improvement of 33.52% in storage cost through the Firebase database, which outperforms existing state-of-the-art schemes. |
format | Online Article Text |
id | pubmed-9886322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98863222023-01-31 Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic Saraswat, Deepti Bhattacharya, Pronaya Shah, Tirth Satani, Rushi Tanwar, Sudeep Procedia Comput Sci Article The Global Novel Coronavirus Disease-2019 (COVID-19) pandemic has forced social distancing norms that have been followed worldwide. Thus, traditional biometric-based attendance marking systems are replaced with contactless attendance marking schemes. However, there are limitations of manufacturing cost, spoofing attacks, and security vulnerabilities. Thus, the paper proposes a contactless camera-based attendance system with the equipped functionalities of anti-spoofing. The proposed scheme can detect liveliness, so fake attendance marking is eliminated. The proposed scheme is also scalable and cost-effective, with generic solutions adaptable to schools, colleges, or other places where attendance is required. The system also eliminates the limitation of one-entry by multiple face-marking systems that allow simultaneous attendance marking. In performance analysis, parameters like image precision, storage cost, retrieval latency, and analysis of the anti-spoofing module is presented against existing schemes. An accuracy of 95.85% is reported for the model, with a significant improvement of 33.52% in storage cost through the Firebase database, which outperforms existing state-of-the-art schemes. The Author(s). Published by Elsevier B.V. 2023 2023-01-31 /pmc/articles/PMC9886322/ /pubmed/36743795 http://dx.doi.org/10.1016/j.procs.2023.01.129 Text en © 2023 The Author(s). Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Saraswat, Deepti Bhattacharya, Pronaya Shah, Tirth Satani, Rushi Tanwar, Sudeep Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic |
title | Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic |
title_full | Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic |
title_fullStr | Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic |
title_full_unstemmed | Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic |
title_short | Anti-spoofing-enabled Contactless Attendance Monitoring System in the COVID-19 Pandemic |
title_sort | anti-spoofing-enabled contactless attendance monitoring system in the covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886322/ https://www.ncbi.nlm.nih.gov/pubmed/36743795 http://dx.doi.org/10.1016/j.procs.2023.01.129 |
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