1 citations · 2 across the 6 of their papers we have counts for
9 papers
End-to-End Verifiable and Robust Federated Learning
Doryan Lesaignoux, Enrique Mármol Campos, Gabriele Spini +2
Federated learning enables multiple parties to train a shared model without centralizing raw data with the help of an aggregator, but introduces integrity risks once participants o…
ICS Cybersecurity Datasets: A Systematic Meta-Review of Coverage, Evaluation Practice, and Structural Gaps
Konstantinos E. Kampourakis, Vyron Kampourakis, Georgios Kambourakis +4
Intrusion detection research in Industrial Control Systems (ICS) heavily depends on public datasets, yet no prior work has systematically assessed whether the collective dataset co…
On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions
Daniel M. Jimenez-Gutierrez, Yelizaveta Falkouskaya, Jose L. Hernandez-Ramos +3
Federated Learning (FL) is an emerging distributed machine learning paradigm enabling multiple clients to train a global model collaboratively without sharing their raw data. While…
Federated Learning for Misbehaviour Detection with Variational Autoencoders and Gaussian Mixture Models
Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos +1
Federated Learning (FL) has become an attractive approach to collaboratively train Machine Learning (ML) models while data sources' privacy is still preserved. However, most of exi…
FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning
Enrique Mármol Campos, Aurora González Vidal, José Luis Hernández Ramos +1
Federated Learning (FL) represents a promising approach to typical privacy concerns associated with centralized Machine Learning (ML) deployments. Despite its well-known advantages…
Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges
Enrique Mármol Campos, Pablo Fernández Saura, Aurora González-Vidal +4
The application of Machine Learning (ML) techniques to the well-known intrusion detection systems (IDS) is key to cope with increasingly sophisticated cybersecurity attacks through…
Sharing pandemic vaccination certificates through blockchain: Case study and performance evaluation
José Luis Hernández-Ramos, Georgios Karopoulos, Dimitris Geneiatakis +3
This work proposes a scalable, blockchain-based platform for the secure sharing of COVID-19 or other disease vaccination certificates. As an indicative use case, we simulate a larg…
Demystifying COVID-19 digital contact tracing: A survey on frameworks and mobile apps
Tania Martin, Georgios Karopoulos, José L. Hernández-Ramos +2
The coronavirus pandemic is a new reality and it severely affects the modus vivendi of the international community. In this context, governments are rushing to devise or embrace no…
Toward a Blockchain-based Platform to Manage Cybersecurity Certification of IoT devices
Ricardo Neisse, José L. Hernández-Ramos, Sara N. Matheu +2
The goal of this paper is to propose a blockchain-based platform to enhance transparency and traceability of cybersecurity certification information motivated by the recently adopt…