6G Security Architecture: AI-Driven Threat Detection and Zero Trust
Dr. Ahmad-Reza Sadeghi, Prof. Gene Tsudik
TU Darmstadt / UC Irvine
Abstract
We propose a comprehensive security architecture for 6G networks that integrates AI-driven threat detection with zero trust principles. The architecture addresses new attack surfaces introduced by 6G technologies including RIS, NTN, and semantic communication. Our AI-based anomaly detection system achieves 99.2% detection rate with a false positive rate below 0.1%, while the zero trust framework reduces the blast radius of successful attacks by 85%.
AI Summary
- Comprehensive 6G security architecture combining AI threat detection and zero trust.
- 99.2% threat detection rate with < 0.1% false positives.
- Zero trust framework reduces attack blast radius by 85%.
- Addresses new 6G-specific attack surfaces (RIS, NTN, semantic communication).
Key Findings
- 16G introduces at least 12 new attack vectors not present in 5G.
- 2AI-driven detection is essential for the speed and scale of 6G threats.
- 3Zero trust must extend from core network to edge and even IoT devices.
Industry Implications
Security must be designed into 6G from the beginning, not added later.
Operators need significant investment in AI security capabilities.
Standardization should include security as a first-class requirement for 6G.
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