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…

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 an open-source 5G testbed for simulating emergency alert spoofing attacks and proposes a cross-cell verification mechanism to detect single-source, potentially fake, warnings.

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…

The paper introduces Devilray, a comprehensive adversarial model that systematically tests the realistic operational space of fake base stations, revealing significant blind spots in existing detectio…

This paper evaluates the security of industrial control systems (ICS) transitioning to 5G communication, finding that while optimal conditions allow for resilience, degraded channel conditions signifi…

The paper investigates undetectable command and control (C2) channels within 5G core networks, demonstrating how compromised components can enable sophisticated attacks against subscriber security and…

This paper demonstrates a non-disruptive, sidecar-based integration of NIST-standardized Post-Quantum Cryptography (PQC) into an open-source 5G core, showing that while it introduces a predictable lat…

The paper proposes a cross-layer behavioral fingerprinting framework that fuses physical and network data to detect comprehensive attacks in dense LEO satellite constellations, achieving high detectio…

CLOUDBURST introduces a novel framework and taxonomy for passive cloud-native beacons, demonstrating that IAM Canary Roles are the most effective vector for real-time threat attribution in modern clou…

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 demonstrates that a specific routing-layer defense mechanism in OLSR-based MANETs can be inferred from passively observable routing and control-plane behavior, even when the defense operate…

The paper analyzes the security and practical deployability of advanced Wi-Fi ranging standards (IEEE 802.11az/bk), concluding that while promising, secure implementation is highly sensitive to config…

The paper introduces PINSIGHT, a novel methodology that rigorously assesses Wi-Fi PIN code inference attacks by separating environmental effects from typing effects, concluding that current state-of-t…

This paper enhances an existing autonomous online Intrusion Detection System (AOC-IDS) for IoT by addressing class imbalance, pseudo-label reliability, and computational overhead, achieving significan…

The paper proposes a federated, high-throughput stream-processing framework for cross-sector threat detection and automated containment, achieving end-to-end operational convergence within 12-20 secon…

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 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 proposes a federated learning framework using FedAvg to detect RF jamming attacks in 5G networks directly from over-the-air IQ samples, achieving high accuracy while maintaining user data p…

MeshGuard is a framework that extends MUD-based network access control to complex, large-scale Thread IoT networks by adapting the MLE protocol and using SDN for scalable policy enforcement.