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Signature-Based Intrusion Detection System in Wireless 6G IoT Networks

Mansoor Farooq1,*, Mubashir Hassan Khan2

1 University of Kashmir, Srinagar, 190003, India
2 Cluster University, Srinagar, 190008, India

* Corresponding Author: Mansoor Farooq. Email: email

Journal on Internet of Things 2022, 4(3), 155-168. https://doi.org/10.32604/jiot.2022.039271

Abstract

An “Intrusion Detection System” (IDS) is a security measure designed to perceive and be aware of unauthorized access or malicious activity on a computer system or network. Signature-based IDSs employ an attack signature database to identify intrusions. This indicates that the system can only identify known attacks and cannot identify brand-new or unidentified assaults. In Wireless 6G IoT networks, signature-based IDSs can be useful to detect a wide range of known attacks such as viruses, worms, and Trojans. However, these networks have specific requirements and constraints, such as the need for real-time detection and low-power operation. To meet these requirements, the IDS algorithm should be designed to be efficient in terms of resource usage and should include a mechanism for updating the attack signatures to keep up with evolving threats. This paper provides a solution for a signature-based intrusion detection system in wireless 6G IoT Networks, in which three different algorithms were used and implemented by using python and JavaScript programming languages and an accuracy of 98.9% is achieved.

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APA Style
Farooq, M., Khan, M.H. (2022). Signature-based intrusion detection system in wireless 6G iot networks. Journal on Internet of Things, 4(3), 155-168. https://doi.org/10.32604/jiot.2022.039271
Vancouver Style
Farooq M, Khan MH. Signature-based intrusion detection system in wireless 6G iot networks. J Internet Things . 2022;4(3):155-168 https://doi.org/10.32604/jiot.2022.039271
IEEE Style
M. Farooq and M.H. Khan, “Signature-Based Intrusion Detection System in Wireless 6G IoT Networks,” J. Internet Things , vol. 4, no. 3, pp. 155-168, 2022. https://doi.org/10.32604/jiot.2022.039271



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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