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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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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1716772681758539776 |