Multibiometric System for Internet of Things using Trust Management

Falmata Modu; Yusuf Sani; Farouq Aliyu; Audu Mabu

doi:10.1109/ICCIS49240.2020.9257709

Multibiometric System for Internet of Things using Trust Management

Falmata Modu
, Yusuf Sani
, Farouq Aliyu
, Audu Mabu

Applied Research Center for Nonprofit and Social Development

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Biometric-based authentication systems are prone to spoofing attacks, errors due to noisy data, intra- and inter-class variations. Combining multiple biometric traits (multibiometric system) promises more accuracy. However, this leads to overhead due to an increase in complexity, form factor, energy and latency in the system. In this paper, a trust management system is used together with a decision level multibiometric system to improve the accuracy and lower the energy consumption of the proposed system. The proposed system is found to drop the false positive rate value by a factor of 4 and the energy consumption was reduced by a factor of 7.

Original language	English
Title of host publication	2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728154671
DOIs	https://doi.org/10.1109/ICCIS49240.2020.9257709
State	Published - 13 Oct 2020

Publication series

Name	2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

Face Recognition
Fingerprint
Internet of Things
Multi-biometric Systems
Trust Management

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Information Systems and Management
Control and Optimization
Information Systems

Access to Document

10.1109/ICCIS49240.2020.9257709

Cite this

Modu, F., Sani, Y., Aliyu, F., & Mabu, A. (2020). Multibiometric System for Internet of Things using Trust Management. In 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020 Article 9257709 (2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCIS49240.2020.9257709

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abstract = "Biometric-based authentication systems are prone to spoofing attacks, errors due to noisy data, intra- and inter-class variations. Combining multiple biometric traits (multibiometric system) promises more accuracy. However, this leads to overhead due to an increase in complexity, form factor, energy and latency in the system. In this paper, a trust management system is used together with a decision level multibiometric system to improve the accuracy and lower the energy consumption of the proposed system. The proposed system is found to drop the false positive rate value by a factor of 4 and the energy consumption was reduced by a factor of 7.",

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author = "Falmata Modu and Yusuf Sani and Farouq Aliyu and Audu Mabu",

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year = "2020",

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doi = "10.1109/ICCIS49240.2020.9257709",

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Modu, F, Sani, Y, Aliyu, F & Mabu, A 2020, Multibiometric System for Internet of Things using Trust Management. in 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020., 9257709, 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICCIS49240.2020.9257709

Multibiometric System for Internet of Things using Trust Management. / Modu, Falmata; Sani, Yusuf; Aliyu, Farouq et al.
2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9257709 (2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Multibiometric System for Internet of Things using Trust Management

AU - Modu, Falmata

AU - Sani, Yusuf

AU - Aliyu, Farouq

AU - Mabu, Audu

PY - 2020/10/13

Y1 - 2020/10/13

N2 - Biometric-based authentication systems are prone to spoofing attacks, errors due to noisy data, intra- and inter-class variations. Combining multiple biometric traits (multibiometric system) promises more accuracy. However, this leads to overhead due to an increase in complexity, form factor, energy and latency in the system. In this paper, a trust management system is used together with a decision level multibiometric system to improve the accuracy and lower the energy consumption of the proposed system. The proposed system is found to drop the false positive rate value by a factor of 4 and the energy consumption was reduced by a factor of 7.

AB - Biometric-based authentication systems are prone to spoofing attacks, errors due to noisy data, intra- and inter-class variations. Combining multiple biometric traits (multibiometric system) promises more accuracy. However, this leads to overhead due to an increase in complexity, form factor, energy and latency in the system. In this paper, a trust management system is used together with a decision level multibiometric system to improve the accuracy and lower the energy consumption of the proposed system. The proposed system is found to drop the false positive rate value by a factor of 4 and the energy consumption was reduced by a factor of 7.

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KW - Multi-biometric Systems

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DO - 10.1109/ICCIS49240.2020.9257709

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T3 - 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020

BT - 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020

PB - Institute of Electrical and Electronics Engineers Inc.

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Modu F, Sani Y, Aliyu F, Mabu A. Multibiometric System for Internet of Things using Trust Management. In 2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9257709. (2020 2nd International Conference on Computer and Information Sciences, ICCIS 2020). doi: 10.1109/ICCIS49240.2020.9257709