4 papers
Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge
Gustavo de Carvalho Bertoli
While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs). This paper presents an empiric…
Privacy-Preserving IoT in Connected Aircraft Cabin
Nilesh Vyas, Benjamin Zhao, Aygün Baltaci +6
The proliferation of IoT devices in shared, multi-vendor environments like the modern aircraft cabin creates a fundamental conflict between the promise of data collaboration and th…
FedFlex: Federated Learning for Diverse Netflix Recommendations
Sven Lankester, Gustavo de Carvalho Bertoli, Matias Vizcaino +2
The drive for personalization in recommender systems creates a tension between user privacy and the risk of "filter bubbles". Although federated learning offers a promising paradig…
Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service Detection
Leonardo Henrique de Melo, Gustavo de Carvalho Bertoli, Michele Nogueira +2
Distributed denial-of-service (DDoS) attacks remain a critical threat to Internet services, causing costly disruptions. While machine learning (ML) has shown promise in DDoS detect…