Securing IoT Environment using Machine Learning Techniques

Autor:	Nasib Singh Gill, Amit Sagu
Přispěvatelé:	Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Environmental Engineering C5339029320/2020©BEIESP business.industry Human–computer interaction Computer science IoT security challenges machine learning General Engineering 2249-8958 Internet of Things business Computer Science Applications
Popis:	One of the most dynamic and invigorate advancement in information technology is advent of Internet of Things (IoT). IoT is territory of interrelated computational and digital devices with intelligence to transfer data. Along with swift expansion of IoT devices through the world security of things is not at expected height. As a consequence of ubiquitous nature of IoT environment most of the user do not have expertise or willingness to secure devices by themselves. Machine learning approach could be very effective to address security challenges in IoT environment. In recent related papers, the researcher have used machine learning techniques, approaches or methods for securing things in IoT environment. This paper attempts to review the related research on machine learning approaches to secure IoT devices.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16999ef22292d1c1aa5b392d62a0a7be https://zenodo.org/record/5573330 Zobrazit plný text záznamu