Secure and Forensic-Aware Edge Intelligence and Open RAN for B5G/6G

Dear Colleagues,

The evolution from fifth-generation mobile systems toward sixth-generation networks is transforming radio access, core networks, and cloud infrastructure. Open RAN architectures, programmable radios, and cloud native cores are enabling flexible deployments and edge intelligence that can bring learning and decision-making closer to users and devices. At the same time, massive machine-type communication, ultra-reliable and low-latency services, and dense Internet of Things environments are creating new expectations for security, privacy, and resilience at the radio, edge, and cloud layers.

These trends require security and privacy mechanisms designed in concert with edge intelligence and Open RAN rather than being added after the fact. There is also a growing need for forensic-aware networks, that is, networks capable of capturing, preserving, and analyzing trustworthy evidence across radio, edge, and cloud environments without violating user privacy or service-level guarantees. Achieving these goals calls for joint advances in wireless communications, distributed learning, cybersecurity, privacy preservation, and digital forensics.

This Special Issue on Secure and Forensic-Aware Edge Intelligence and Open RAN for B5G/6G aims to provide a forum for recent research results, practical deployments, and visionary perspectives in this area. We welcome contributions that address, among other topics, security and privacy in Open RAN and softwarized radio access, learning-based and federated security at the edge, privacy-preserving analytics for radio and Internet of Things data, digital forensics methods for cloud native and edge platforms, secure orchestration and automation across radio, edge, and core networks, and testbeds, prototypes, and case studies that demonstrate secure and forensic-aware Open RAN and edge intelligent solutions.

Topics of interest include, but are not limited to the following:

• Security, privacy, and trust in Open RAN (O-RAN) and softwarized RAN architectures;
• AI-/ML- and federated-learning-based security for RAN, edge, and IoT networks (intrusion detection, anomaly detection, threat hunting);
• Zero-trust, secure orchestration, and slice isolation in B5G/6G networks with Open RAN and edge intelligence;
• Digital forensics for cloud-native RAN, edge computing platforms, and large-scale IoT deployments;
• Privacy-preserving analytics and distributed learning for radio, edge, and IoT data;
• Security and reliability in cognitive radio, dynamic spectrum access, and wireless sensor networks;
• Multi-objective optimization of performance, energy efficiency, and security in Open RAN and edge-intelligent systems;
• Case studies, testbeds, datasets, and benchmark frameworks for secure and trustworthy Open RAN and edge intelligence.

We invite original research papers, survey and tutorial articles, and application-oriented contributions from both academia and industry. Our goal is to help shape the next generation of secure, privacy-preserving, and forensic-ready Open RAN and edge intelligent networks for beyond fifth-generation and sixth-generation communication systems.

Dr. Pasika Sashmal Ranaweera
Dr. Ranul Thantilage
Dr. Indika A. M. Balapuwaduge
Guest Editors

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• open RAN
• B5G and 6G networks
• edge intelligence
• security and privacy
• digital forensics
• forensic-aware networking
• federated learning
• internet of things and wireless sensor networks
• network softwarization