Chamara posts
Netslab-5GORAN-IDD
The Netslab-5G Open RAN Intrusion Detection Dataset (Netslab-5GORAN-IDD) is a real-world dataset collected using a physical 5G Open RAN testbed at University College Dublin. It
Federated Learning for 6G Networks: Navigating Privacy Benefits and Challenges
The upcoming Sixth Generation (6G) networks aim for fully automated, intelligent network functionalities and services. Therefore, Machine Learning (ML) is essential for these networks. Given
DisLLM: Distributed LLMs for Privacy Assurance in Resource-Constrained Environments
Large Language Models (LLMs) have revolutionized natural language processing, but deploying them in resource-constrained environments and privacy-sensitive domains remains challenging. This paper introduces the Distributed
A survey on privacy of personal and non-personal data in B5G/6G networks
The upcoming Beyond 5G (B5G) and 6G networks are expected to provide enhanced capabilities such asultra-high data rates, dense connectivity, and high scalability. It opens
SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks
With the rapid progression of communication and localisation of big data over billions of devices, distributed Machine Learning (ML) techniques are emerging to cater for
Rec-Def: A Recommendation-based Defence Mechanism for Privacy Preservation in Federated Learning Systems
An emergence of attention and regulations on consumer privacy can be observed over the recent years with the ubiquitous availability of IoT systems handling personal
Bartlomiej posts
RRC Signalling Storm Dataset
Using a real physical O-RAN testbed with real attack execution, this dataset captures information found in different layers in O-RAN. Beyond the traditional approach of
A survey on privacy of personal and non-personal data in B5G/6G networks
The upcoming Beyond 5G (B5G) and 6G networks are expected to provide enhanced capabilities such asultra-high data rates, dense connectivity, and high scalability. It opens
SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks to Defend Against Data Poisoning Attacks
With the rapid progression of communication and localisation of big data over billions of devices, distributed Machine Learning (ML) techniques are emerging to cater for
H2020 ROBUST-6G Kick-off meeting
The 4th consortium meeting for the HORIZON 2020 SPATIAL project was hosted by UCD on the 12th of September 2023. The SPATIAL aims to tackle
Rec-Def: A Recommendation-based Defence Mechanism for Privacy Preservation in Federated Learning Systems
An emergence of attention and regulations on consumer privacy can be observed over the recent years with the ubiquitous availability of IoT systems handling personal
From Opacity to Clarity: Leveraging XAI for Robust Network Traffic Classification
A wide adoption of Artificial Intelligence (AI) can be observed in recent years over networking to provide zero-touch, full autonomy of services towards the next