A Cross-Layer Biometric Recognition System For Mobile Iot Devices

Keywords

Biometric recognition system; Counter-terrorism; Hardware trojan; Internet of things; Security; Surveillance

Abstract

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.

Publication Date

2-24-2018

Publication Title

Electronics (Switzerland)

Volume

7

Issue

2

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.3390/electronics7020026

Socpus ID

85042720233 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85042720233

This document is currently not available here.

Share

COinS