arXiv subjects

Nitin Rajput

Publications and source records attributed to Nitin Rajput.

3 recordsLinked to original sources

arXiv2026

Comparing UPF Dataplane I/O Modes in a Cloud-Native 5G Core: AF_PACKET, AF_XDP, CNDP, and DPDK on SD-Core BESS-UPF

The User Plane Function (UPF) carries all user-plane traffic in a 5G network, and its throughput depends on how packets move between the NIC and the application, that is, on the packet I/O mode. We compare four widely used modes, AF_PACKET, AF_XDP, the Cloud Native Data Plane (CNDP), and the Data Plane Development Kit (DPDK), on a single open-source UPF. Using SD-Core BESS-UPF deployed as a Charmed operator on Intel XXV710 NICs in Canonical Kubernetes, we run the same GTP-U/PDR/FAR/QER pipeline under each mode and change only the BESS port driver, so any difference is attributable to the I/O backend. For each mode we describe its architecture, datapath, memory model, and deployment requirements, and we measure throughput, latency, CPU usage, and stability; the deployment is also validated end-to-end against a disaggregated O-RAN 5G RAN with a commercial UE. On an XXV710/i40e testbed (NDR per RFC 2544) at 64 B, AF_PACKET reaches 0.25 Mpps, CNDP 5.52 and AF_XDP 6.47 Mpps at 2 workers, and DPDK 10.30 Mpps at 4 workers and 13.09 at 8, with the lowest latency (8.1 microseconds average). At matched worker counts the three kernel-bypass modes are within noise and AF_XDP leads per core; DPDK's advantage is a scaling-ceiling effect, since its native PMD over vfio-pci escapes the per-netdev AF_XDP socket limit that pins CNDP and AF_XDP at two workers, not a per-packet efficiency win. CNDP and AF_XDP are the cloud-native sweet spot when hugepages, vfio-pci, and isolated cores are unaffordable; DPDK is justified on dedicated hosts. We also document deployment pitfalls absent from synthetic benchmarks, including a Kubernetes limits.cpu mis-setting that silently halved DPDK throughput. The paper is a side-by-side reference for operators choosing a UPF dataplane mode in a cloud-native 5G deployment.

cs.NI↗

arXiv2025

Q-RAN: Quantum-Resilient O-RAN Architecture

The telecommunications industry faces a dual transformation: the architectural shift toward Open Radio Access Networks (O-RAN) and the emerging threat from quantum computing. O-RAN disaggregated, multi-vendor architecture creates a larger attack surface vulnerable to crypt-analytically relevant quantum computers(CRQCs) that will break current public key cryptography. The Harvest Now, Decrypt Later (HNDL) attack strategy makes this threat immediate, as adversaries can intercept encrypted data today for future decryption. This paper presents Q-RAN, a comprehensive quantum-resistant security framework for O-RAN networks using NIST-standardized Post-Quantum Cryptography (PQC). We detail the implementation of ML-KEM (FIPS 203) and ML-DSA (FIPS 204), integrated with Quantum Random Number Generators (QRNG) for cryptographic entropy. The solution deploys PQ-IPsec, PQ-DTLS, and PQ-mTLS protocols across all O-RAN interfaces, anchored by a centralized Post-Quantum Certificate Authority (PQ-CA) within the SMO framework. This work provides a complete roadmap for securing disaggregated O-RAN ecosystems against quantum adversaries.

cs.CR↗

arXiv2025

QORE : Quantum Secure 5G/B5G Core

Quantum computing is reshaping the security landscape of modern telecommunications. The cryptographic foundations that secure todays 5G systems, including RSA, Elliptic Curve Cryptography (ECC), and Diffie-Hellman (DH), are all susceptible to attacks enabled by Shors algorithm. Protecting 5G networks against future quantum adversaries has therefore become an urgent engineering and research priority. In this paper we introduce QORE, a quantum-secure 5G and Beyond 5G (B5G) Core framework that provides a clear pathway for transitioning both the 5G Core Network Functions and User Equipment (UE) to Post-Quantum Cryptography (PQC). The framework uses the NIST-standardized lattice-based algorithms Module-Lattice Key Encapsulation Mechanism (ML-KEM) and Module-Lattice Digital Signature Algorithm (ML-DSA) and applies them across the 5G Service-Based Architecture (SBA). A Hybrid PQC (HPQC) configuration is also proposed, combining classical and quantum-safe primitives to maintain interoperability during migration. Experimental validation shows that ML-KEM achieves quantum security with minor performance overhead, meeting the low-latency and high-throughput requirements of carrier-grade 5G systems. The proposed roadmap aligns with ongoing 3GPP SA3 and SA5 study activities on the security and management of post-quantum networks as well as with NIST PQC standardization efforts, providing practical guidance for mitigating quantum-era risks while safeguarding long-term confidentiality and integrity of network data.

cs.CR↗