# AI for Beyond 5G Networks: A Cyber-Security Defense or Offense Enabler?

arXiv: https://arxiv.org/abs/2201.02730 · HTML: https://mlsanity.com/paper/2201.02730/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jan 2022.

## Built on by (most cited first, 5 of 5)

- [Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis](https://mlsanity.com/paper/2502.21286/) (2025)
- [Towards Secure Intelligent O-RAN Architecture: Vulnerabilities, Threats and Promising Technical Solutions using LLMs](https://mlsanity.com/paper/2411.08640/) (2024)
- [Towards Zero Touch Networks: Cross-Layer Automated Security Solutions for 6G Wireless Networks](https://mlsanity.com/paper/2502.20627/) (2025)
- [Contextualized AI for Cyber Defense: An Automated Survey using LLMs](https://mlsanity.com/paper/2409.13524/) (2024)
- [Deep Edge Intelligence: Architecture, Key Features, Enabling Technologies and Challenges](https://mlsanity.com/paper/2210.12944/) (2022)

## Abstract (arXiv)

Artificial Intelligence (AI) is envisioned to play a pivotal role in empowering intelligent, adaptive and autonomous security management in 5G and beyond networks, thanks to its potential to uncover hidden patterns from a large set of time-varying multi-dimensional data, and deliver faster and accurate decisions. Unfortunately, AI's capabilities and vulnerabilities make it a double-edged sword that may jeopardize the security of future networks. This paper sheds light on how AI may impact the security of 5G and its successive from its posture of defender, offender or victim, and recommends potential defenses to safeguard from malevolent AI while pointing out their limitations and adoption challenges.