INTELLIGENT AND TRUSTWORTHY 6G: AI-DRIVEN ARCHITECTURES, APPLICATIONS, AND SECURITY FRAMEWORKS

Authors: Mohd Abdul Raheem & Mohammed Azmath Ansari

ABSTRACT

Compared to 5G, the sixth generation (6G) wireless network offers ultra-low latency, great reliability, a large connection, integrated sensing, and seamless intelligence. Artificial intelligence (AI) is positioned as a key architectural pillar of 6G, as opposed to merely an enabler, in contrast to previous generations. Using distributed intelligence, edge-cloud synergy, and data-driven control planes as architectural foundations, this study explores the basic integration of AI across the 6G network stack. These allow for self-configuring, autonomous networks where embedded AI agents make proactive, adaptive decisions in a variety of dynamic, diverse environments. It is well known that Explainable AI (XAI) increases confidence and transparency in critical processes like resource management, slicing, and anomaly detection. Important applications include QoE optimization, integrated sensing and communication, intelligent beamforming for terahertz communications, and real-time traffic prediction. Security and privacy challenges are addressed through federated learning, differential privacy, secure multiparty computation, and blockchain-based mechanisms. The article also reviews major initiatives from organizations and vendors driving interoperable and standardizable AI frameworks for 6G deployment. Ultimately, AI is positioned as the driving force behind intelligent, secure, and sustainable 6G systems, while future research must focus on robustness, ethical frameworks, transparency, and interdisciplinary collaboration.

Keywords: 6G Networks, Artificial Intelligence (AI), Network Intelligence, Explainable AI (XAI), Network Slicing, Autonomous Networks, Security, Privacy, Federated Learning, Blockchain, Edge Intelligence, ISAC, Reinforcement Learning, Trustworthy AI, 6G Architecture, Self-Organizing Networks.

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