AI/ML for 5G and Beyond Cybersecurity
Sandeep Pirbhulal, Habtamu Abie, Martin Jullum, Didrik Nielsen, and Anders L{\o}land

TL;DR
This paper reviews the role of AI/ML in enhancing security for 5G and beyond IoT systems, emphasizing the need for trustworthy AI/ML deployment and proposing perspectives for threat prediction and mitigation.
Contribution
It provides a comprehensive review of AI/ML applications in 5G security and offers perspectives on predicting and mitigating security threats in future networks.
Findings
AI/ML techniques are vital for cybersecurity in 5G and IoT.
Challenges exist in defining and understanding AI/ML-specific threats.
Real-time monitoring is essential for security in 5G and beyond.
Abstract
The advancements in communication technology (5G and beyond) and global connectivity Internet of Things (IoT) also come with new security problems that will need to be addressed in the next few years. The threats and vulnerabilities introduced by AI/ML based 5G and beyond IoT systems need to be investigated to avoid the amplification of attack vectors on AI/ML. AI/ML techniques are playing a vital role in numerous applications of cybersecurity. Despite the ongoing success, there are significant challenges in ensuring the trustworthiness of AI/ML systems. However, further research is needed to define what is considered an AI/ML threat and how it differs from threats to traditional systems, as currently there is no common understanding of what constitutes an attack on AI/ML based systems, nor how it might be created, hosted and propagated [ETSI, 2020]. Therefore, there is a need for…
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Taxonomy
TopicsInternet of Things and AI · Blockchain Technology Applications and Security · Smart Grid Security and Resilience
