Investigating Use of Kinds of Deep Learning Methods in Internet of Things Networks Security
Subject Areas : Computer Engineering
Hadi Mahdavinia
1
,
Mohammadreza Soltanaghaei
2
,
Mahdi Esmaeili
3
1 - Department of Computer Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Khorasgan, Isfahan, Iran
2 - Department of Computer Engineering, Isfahan (Khorasgan) Branch, Islamic Azad University, Khorasgan, Isfahan, Iran
3 - Department of Computer Engineering, Kashan Branch, Islamic Azad University, Kashan, Isfahan, Iran
Keywords: Deep learning methods, Network security, Internet of things, Internet of things security, Deep learning approaches,
Abstract :
The development of smart devices in many aspects of our daily lives is accompanied by the increasing use of appropriate mechanisms to counter them against various attacks and applications in the Internet of Things environment. In this context, it is emerging as one of the most successful and suitable techniques for use in various aspects of IoT security. The aim of this is to systematically review and analyze research studies on research eyes conducted in different Internet of Things security scenarios. The reviewed researches are classified according to different perspectives in a coherent and structured classification to identify the gap in this research area. This research has been published on articles related to the keywords "concept learning", "security" and "Internet of Things" in the four main databases IEEEXplore, ScienceDirect, SpringerLink, and ACM Digital Library. In the end, 90 articles have been selected and reviewed. These studies are conducted according to three main research questions, i.e. the security aspects involved, the network architectures used, and the datasets used in IoT security. The final discussion explores the research gaps and acknowledges the outstanding flaws and vulnerabilities in the IoT security scenario.
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