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A Deep Study of Novel Intrusion Detection Systems and Intrusion Prevention Systems for Internet of Things Networks.
- Source :
- Procedia Computer Science; 2022, Vol. 210, p94-103, 10p
- Publication Year :
- 2022
-
Abstract
- Nowadays, the Internet of Things (IoT) environments are evolving and becoming popular. The number of devices connected to the Internet continues to raise. IoT is an interrelated network of numerous devices in which data is automatically gathered from the environment by the sensors and transferred over the internet without human support and intervention. The IoT eases individuals interacting with real-world applications over the internet in the IoT environment. Modern innovations in IoT have added computers, sensors, streets, buildings, and even communities to the impression of smartness. IoT appliances function in distinct environments to fulfill several purposes; result in the variety of computational devices and communication technologies employed in healthcare, education, military, agriculture, and commerce. Thus, IoT holds a lot of promise for enhancing social and corporate life. Nevertheless, IoT equipment are a soft target and prone to attacks due substantially to their resource limitations, and the nature of their networks. There are many approaches and technologies utilized to preclude IoT from varied attacks and assaults, Intrusion Detection System (IDS) and Intrusion Preventions System (IPS) are some of them, which can ensure the security, privacy, and reliability of the IoT. In this paper, we provide a deep study of many recent and pertinent IDS/IPS proposed between 2019 and 2022 for IoT networks, giving their key specifics, strengths, shortcomings, and challenges in order to spot the issues that still require to be handled. The paper also lines the mainstream research direction and opens the way for new avenues of research for forthcoming researchers. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 18770509
- Volume :
- 210
- Database :
- Supplemental Index
- Journal :
- Procedia Computer Science
- Publication Type :
- Academic Journal
- Accession number :
- 160212626
- Full Text :
- https://doi.org/10.1016/j.procs.2022.10.124