Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks
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Abstract (arXiv)
As global Internet of Things (IoT) devices connectivity surges, a significant portion gravitates towards the Edge of Things (EoT) network. This shift prompts businesses to deploy infrastructure closer to end-users, enhancing accessibility. However, the growing EoT network expands the attack surface, necessitating robust and proactive security measures. Traditional solutions fall short against dynamic EoT threats, highlighting the need for proactive and intelligent systems. We introduce a digital twin-empowered smart attack detection system for 6G EoT networks. Leveraging digital twin and edge computing, it monitors and simulates physical assets in real time, enhancing security. An online learning module in the proposed system optimizes the network performance. Our system excels in proactive threat detection, ensuring 6G EoT network security. The performance evaluations demonstrate its effectiveness, robustness, and adaptability using real datasets.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Oct 2023.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 1.
4 papers.
- 2024Review of Generative AI Methods in Cybersecuritycited by 9
- 2023LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computationcited by 4
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networkscited by 3
- 2024Global Spatio-Temporal Fusion-based Traffic Prediction Algorithm with Anomaly Awarecited by 0
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks26 Aug 2025
- 2024Global Spatio-Temporal Fusion-based Traffic Prediction Algorithm with Anomaly Aware19 Dec 2024
- 2024Review of Generative AI Methods in Cybersecurity13 Mar 2024
- 2023LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computation17 Dec 2023