This paper provides a comprehensive review of the security vulnerabilities and privacy challenges inherent in the Open Radio Access Network (O-RAN) architecture for the 6G era, systematically categori…

This paper proposes a protocol framework for making the 6G air interface AI-native, focusing on interoperability and preserving implementation freedom.

The paper proposes Q-FE, a novel Quantum-Native 6G Far-Edge architecture that secures Industrial IoT Digital Twins by integrating micro-digital twins, compact post-quantum key exchange, and asynchrono…

This paper proposes an architecture for privacy-preserving intent fulfilment and assurance in 6G networks using a coordinator and aggregate PM counters.

This paper surveys model forensics in AI-native wireless networks, detailing key security problems and demonstrating practical workflows for verifying model authenticity and detecting malicious functi…

This paper argues for a new approach to designing sixth-generation mobile networks, prioritizing control, customer outcomes, business guarantees, software-driven operations, and technology.

This paper proposes a new communication framework, TokCom, for 6G wireless networks where tokens from large language models become the fundamental entities for information exchange.

This paper proposes a covert communications and computations approach to enhance security and efficiency of large language model-enabled edge networks.

The paper proposes a declarative, autonomous, self-protecting framework for securing complex 5G/6G networks by leveraging a standardized security ontology and automated graph reasoning to neutralize l…

This paper provides the first comprehensive review of threats and defenses specifically targeting on-device AI inference, revealing a significant imbalance where certain attack types, like adversarial…

This paper experimentally demonstrates the high detection performance of machine learning-based intrusion detection systems for identifying cyberattacks targeting OPC UA applications running over priv…

This paper proposes Autogenic network management, a self-programming extension to agentic AI for next-generation network management in 6G networks.

This paper proposes a lightweight, multi-layer Machine Learning-based security framework for Industrial IoT (IIoT) to enhance trust convergence and detect advanced threats.

The paper introduces Constraint-Guided Semantic Testing (ConSeT), a novel framework that systematically finds critical, pre-authentication vulnerabilities in 5G User Equipment (UE) by exploiting seman…

This paper presents a tutorial-and-survey on integrating agentic AI into Next-Generation Networks (NGNs), addressing the gap in protocol integration, evaluation, and standardization alignment.

This paper proposes SubEdge, a Net4AI subsystem for per-subscriber edge computing and communication resource provisioning, ensuring service continuity during mobility.

This paper surveys information-theoretic approaches to secure Integrated Sensing and Communication (ISAC), providing a comprehensive review of models, security formulations, and fundamental limits.

This paper proposes a cloud-edge-end collaborative defense framework to secure UAV swarms against various threats like GPS spoofing and multi-hop intrusions, demonstrating its effectiveness through ex…

The paper proposes ExAI5G, a logic-based explainable AI framework that integrates a Transformer-based IDS with XAI techniques to provide highly accurate and transparent intrusion detection for 5G netw…

This paper synthesizes the emerging field of blockchain and AI for securing intelligent networks by providing a comprehensive taxonomy, integration patterns, and an evaluation blueprint.