A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges

Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as develo...

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Vydané v:Archives of computational methods in engineering Ročník 28; číslo 4; s. 3211 - 3243
Hlavní autori: Thakkar, Ankit, Lohiya, Ritika
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Netherlands 01.06.2021
Springer Nature B.V
Predmet:
Applications programs
Deep learning
Domains
Electronic devices
Engineering
Firewalls
Intelligent networks
Internet of Things
Intrusion detection systems
Machine learning
Mathematical and Computational Engineering
Original Paper
Security management
Smart buildings
Smart grid
Smart grid technology
Wireless networks
Wireless sensor networks
ISSN:1134-3060, 1886-1784
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Popis
Shrnutí:Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as developing smart home, smart cities, healthcare applications, wireless sensor networks, cloud environment, enterprise network, web applications, and smart grid technologies. These wide emerging applications in variety of domains raise many security issues such as protecting devices and network, attacks in IoT networks, and managing resource-constrained IoT networks. To address the scalability and resource-constrained security issues, many security solutions have been proposed for IoT such as web application firewalls and intrusion detection systems. In this paper, a comprehensive survey on Intrusion Detection System (IDS) for IoT is presented for years 2015–2019. We have discussed various IDS placement strategies and IDS analysis strategies in IoT architecture. The paper discusses various intrusions in IoT, along with Machine Learning (ML) and Deep Learning (DL) techniques for detecting attacks in IoT networks. The paper also discusses security issues and challenges in IoT.
Bibliografia:ObjectType-Article-1
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ISSN:1134-3060
1886-1784
DOI:10.1007/s11831-020-09496-0