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Title	Smart Hardware Trojan Detection System
ID_Doc	50999
Authors	Alkhazendar I.; Zubair M.; Qidwai U.
Year	2023
Published	Lecture Notes in Networks and Systems, 544 LNNS
DOI	http://dx.doi.org/10.1007/978-3-031-16075-2_58
Abstract	The IoT has become an indispensable part of human lives at work and home applications. Due to the need for an enormous number of IoT devices manufacturers are least concerned about security vulnerabilities during designing and developing of these devices. Because of this, it becomes easier for adversaries to manipulate the hardware and insert Trojans or Remote File Inclusion to control remotely. In this research, we aim to build a model to identify hardware Trojans in IoT devices using Deep learning. We used different machine learning models to evaluate the performance and accuracy. In addition we choose a distinctive feature that can detect the presence of Trojan in these devices. The proposed model is evaluated using an existing and real-time dataset generated using a smart city testbed, The testbed used was designed to simulate and evaluate the Hardware trojan attacks, and by using the real-time dataset we could measure the power profile and network traffic on the IoT gateway device to analyze the performance and the accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Author Keywords	DOS attack; Hardware Trojan; Internet of Things; Smart cities; Smart detection system

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