Papers for
telecommunications infrastructure engineers
Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.
Security risks found in 6G and O-RAN networks with open interfaces
Security evaluation of 6G-oriented and O-RAN networks through targeted attacks
Abstract: The sixth generation (6G) of networks is supported by increased bandwidth, automation through the use of O-RAN technologies. Simultaneously though autonomous operation leads to an extensive threat surface and sophisticated attacks. Understanding the attack impact, the Tactics, Techniques and Procedures that are used by attackers is extremely challenging, but however is crucial for developing defense and mitigation strategies against them. This paper evaluates a targeted attack chain against a virtualized, 6G-oriented O-RAN testbed in which the F1 midhaul interface is accessible to an attacker and transport-layer protection is not enabled. The attack disrupts the legitimate O-DU association, introduces a rogue O-DU using observed configuration parameters, and intercepts user-plane traffic. The attack was evaluated in a fully virtualized testbed based on Open5GS, the srsRAN Project, FlexRIC, and an Electric Vehicle (EV) charging infrastructure based on OCPP 1.6.
Combining quantum safe cryptography and quantum key distribution to protect data
Combining Post-Quantum Cryptography and Quantum Key Distribution: Taxonomy, Constructions, Proofs, Standards, Deployments and Open Problems
Abstract: Post-quantum cryptography (PQC) and quantum key distribution (QKD) address the quantum threat from opposite directions: PQC replaces vulnerable public-key algorithms with schemes believed to resist quantum cryptanalysis, while QKD derives keys whose secrecy rests on physical assumptions rather than computational ones. Because each approach has a distinct failure mode, a growing body of work combines them so that a session key remains secure if either component holds. We first establish the deployed baseline, hybrid classical-plus-PQC key exchange, against which QKD-augmented designs must be judged. We then propose a taxonomy of hybrid PQC-QKD designs along eight dimensions (integration layer, combiner construction, authentication scope and source, QKD topology, trusted entities, key-delivery interface, classical component, and evidence type), and use it to compare published protocols, including Muckle and its successors, MACsec and TLS integrations, and IKEv2 mechanisms standardised in RFCs 8784, 9370, and 9867. We examine key-combiner constructions in light of the KEM-combiner literature and of NIST, ETSI, and ITU-T guidance, and map the security arguments for hybrid PQC-QKD protocols onto a common grid of security model, assumptions, permitted compromise, established guarantee, and limitations. We synthesise deployment evidence from metropolitan and national QKD networks, distinguishing the few testbeds that have run PQC in the key path from pure-QKD deployments, and summarise the standards and policy landscape, including the positions of national security agencies that recommend against relying on QKD alone. We close with open problems: authentication of the QKD classical channel, shared-infrastructure threat models, device certification versus formal proofs, formal verification of hybrid handshakes, and the lack of peer-reviewed deployment economics.
Power-efficient 5G networks save energy by managing layers separately
ALARM: Adaptive Layer-Aware Resource Management for Power-Efficient vRANs
Abstract: The transition to virtualized Radio Access Networks (vRAN) enables dynamic power control through fine-grained CPU resource management. However, existing approaches treat gNB as a monolithic entity, failing to exploit the heterogeneous computational characteristics of different protocol layers. This paper proposes ALARM, a layer-aware adaptive resource management framework for constrained 5G vRAN. ALARM decomposes the gNB into functional layers representing distinct RAN tasks with heterogeneous computational demands, and controls CPU resources at the layer level based on processing weights. The framework monitors per-layer performance to detect violations and responds by scaling only the affected layer. This targeted adaptation avoids the over-provisioning inherent in traditional uniform scaling approaches. Experimental validation on two constrained platforms demonstrates up to 33% power reduction versus non-optimized baseline and 19% beyond uniform approaches, with dynamic adaptation achieving 9.8% additional savings while preserving strict real-time guarantees.