A Cross-Layer Biometric Recognition System for Mobile IoT Devices

A biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target o...

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Main Authors: Shayan Taheri, Jiann-Shiun Yuan
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Electronics
Subjects:
Online Access:http://www.mdpi.com/2079-9292/7/2/26
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spelling doaj-8e56d259ca3a4e6c928cb347bb8aed8d2020-11-24T21:03:53ZengMDPI AGElectronics2079-92922018-02-01722610.3390/electronics7020026electronics7020026A Cross-Layer Biometric Recognition System for Mobile IoT DevicesShayan Taheri0Jiann-Shiun Yuan1Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USADepartment of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USAA biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target of adversaries for accomplishing various malicious scenarios such as disabling the camera in critical times or the lack of recognition of a criminal. In this work, we propose a cross-layer biometric recognition system that has small computational complexity and is suitable for mobile Internet of Things (IoT) devices. Furthermore, due to the involvement of both hardware and software in realizing this system in a decussate and chaining structure, it is easier to locate and provide alternative paths for the system flow in the case of an attack. For security analysis of this system, one of the elements of this system named the advanced encryption standard (AES) is infected by four different Hardware Trojansthat target different parts of this module. The purpose of these Trojans is to sabotage the biometric data that are under process by the biometric recognition system. All of the software and the hardware modules of this system are implemented using MATLAB and Verilog HDL, respectively. According to the performance evaluation results, the system shows an acceptable performance in recognizing healthy biometric data. It is able to detect the infected data, as well. With respect to its hardware results, the system may not contribute significantly to the hardware design parameters of a surveillance camera considering all the hardware elements within the device.http://www.mdpi.com/2079-9292/7/2/26biometric recognition systemcounter-terrorismHardware TrojanInternet of Thingssecuritysurveillance
collection DOAJ
language English
format Article
sources DOAJ
author Shayan Taheri
Jiann-Shiun Yuan
spellingShingle Shayan Taheri
Jiann-Shiun Yuan
A Cross-Layer Biometric Recognition System for Mobile IoT Devices
Electronics
biometric recognition system
counter-terrorism
Hardware Trojan
Internet of Things
security
surveillance
author_facet Shayan Taheri
Jiann-Shiun Yuan
author_sort Shayan Taheri
title A Cross-Layer Biometric Recognition System for Mobile IoT Devices
title_short A Cross-Layer Biometric Recognition System for Mobile IoT Devices
title_full A Cross-Layer Biometric Recognition System for Mobile IoT Devices
title_fullStr A Cross-Layer Biometric Recognition System for Mobile IoT Devices
title_full_unstemmed A Cross-Layer Biometric Recognition System for Mobile IoT Devices
title_sort cross-layer biometric recognition system for mobile iot devices
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2018-02-01
description A biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target of adversaries for accomplishing various malicious scenarios such as disabling the camera in critical times or the lack of recognition of a criminal. In this work, we propose a cross-layer biometric recognition system that has small computational complexity and is suitable for mobile Internet of Things (IoT) devices. Furthermore, due to the involvement of both hardware and software in realizing this system in a decussate and chaining structure, it is easier to locate and provide alternative paths for the system flow in the case of an attack. For security analysis of this system, one of the elements of this system named the advanced encryption standard (AES) is infected by four different Hardware Trojansthat target different parts of this module. The purpose of these Trojans is to sabotage the biometric data that are under process by the biometric recognition system. All of the software and the hardware modules of this system are implemented using MATLAB and Verilog HDL, respectively. According to the performance evaluation results, the system shows an acceptable performance in recognizing healthy biometric data. It is able to detect the infected data, as well. With respect to its hardware results, the system may not contribute significantly to the hardware design parameters of a surveillance camera considering all the hardware elements within the device.
topic biometric recognition system
counter-terrorism
Hardware Trojan
Internet of Things
security
surveillance
url http://www.mdpi.com/2079-9292/7/2/26
work_keys_str_mv AT shayantaheri acrosslayerbiometricrecognitionsystemformobileiotdevices
AT jiannshiunyuan acrosslayerbiometricrecognitionsystemformobileiotdevices
AT shayantaheri crosslayerbiometricrecognitionsystemformobileiotdevices
AT jiannshiunyuan crosslayerbiometricrecognitionsystemformobileiotdevices
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