A collection of academic papers / Git repos / conference talks / frameworks / tools related to cellular security and privacy.

This advanced and complex project implements an AI-powered optimization system for 5G Open RAN networks. Using machine learning and deep learning, the system optimizes network performance by detecting anomalies, predicting network traffic, and dynamically allocating resources.

An O-RAN compliant runtime intrusion detection system (xApp) for layer-3 (L3) celluar attack detection

A module that can be used to model and simulate O-RAN-like behavior in ns-3.

5G gNodeB Centralized Unit written in Rust

MATLAB-based testing tools for the srsRAN Project https://github.com/srsran/srsRAN_Project

Intent driven security automation framework

Python Sample App for SMO Systems like Ericsson Intelligent Automation Platform. We aim to be ORAN aligned. Use this to kickstart your own app!

Traffic Steering (TS) xApp for OAIC O-RAN Testbed

An O-RAN compliant xApp employing deep learning to detect 5G cellular network threats and anomalies

RAN Fusion a NextG RAN Simulator

This project is an LLM-Enhanced Nephio R5 and O-RAN Network Automation System. It integrates a Large Language Model with Nephio's intent-based automation to provide a natural language interface for managing and orchestrating telecommunications network functions.

Offline Federated RL for O-RAN slice resource management on Colosseum traces

Go Sample App for SMO Systems like Ericsson Intelligent Automation Platform. We aim to be ORAN aligned. Use this to kickstart your own app!

Repository to hold security intents in standard template format.

An O-RAN compliant xApp supporting fine-grained and security-aware statistics monitoring over 5G RAN and UEs

xApp for QoS management in O-RAN network contexts

Framework of the dApps. Partially supported by OUSD(R&E) through Army Research Laboratory Cooperative Agreement Number W911NF-24-2-0065, by the O-RAN ALLIANCE, by the SERICS (PE00000014) 5GSec project under the MUR PNRR funded by the European Union — NextGenerationEU, and by the U.S. NSF under grants CNS-1925601, CNS-2117814, and CNS-2112471.

Performance evaluation of several DRL algorithms in a discrete action-space for resource allocation in Open RAN