Version 1
: Received: 14 May 2024 / Approved: 15 May 2024 / Online: 16 May 2024 (08:08:39 CEST)
How to cite:
Gupta, M.; Jha, R. K.; Sabraj, M. Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives. Preprints2024, 2024051066. https://doi.org/10.20944/preprints202405.1066.v1
Gupta, M.; Jha, R. K.; Sabraj, M. Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives. Preprints 2024, 2024051066. https://doi.org/10.20944/preprints202405.1066.v1
Gupta, M.; Jha, R. K.; Sabraj, M. Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives. Preprints2024, 2024051066. https://doi.org/10.20944/preprints202405.1066.v1
APA Style
Gupta, M., Jha, R. K., & Sabraj, M. (2024). Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives. Preprints. https://doi.org/10.20944/preprints202405.1066.v1
Chicago/Turabian Style
Gupta, M., Rakesh Kumar Jha and Manish Sabraj. 2024 "Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives" Preprints. https://doi.org/10.20944/preprints202405.1066.v1
Abstract
The vast network of interconnected devices of the Internet of Things poses significant security challenges, necessitating the upgrade of current wireless networks to the 6G standard and an improved intrusion detection system for host networks. Thus this article therefore underscores a game theory concept to analyze the security impediments in wireless communication systems, where a host network bandwidth is jeopardized by the intruder while acting as a legitimate user. While game theory can help with the impending security concerns, network slicing is saliently proposed for large and complicated networks, precipitating a layer wise fragmentation of the concerned network and effectively addressing the security issues in different layers of the IoT framework. However, with increasing network complexity, network security issues incorporating traditional measures become increasingly cumbersome. Therefore, this paper also briefly mentions some of the ML techniques that can be used to classify and segregate valid users from the compromised nodes in the host network. The paper discusses the potential of incorporating intelligence into wireless communication systems to enhance the host network security. The paper further aids in analyzing existing security issues in different layers of wireless communication systems, underscoring network slicing for further classification of intruders from user nodes and training the host network using ML/AI per the user application specification.
Keywords
6G; Bandwidth spoofing; Game theory; Intrusion detection system (IDS); ML; Network slicing; Security
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
