Enhanced federated anomaly detection through autoencoders using summary statistics-based thresholding
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-76961-2
Abstract: In Federated Learning, Anomaly Detection poses significant challenges due to the decentralized nature of data, especially under Non-IID distributions. This study proposes a federated threshold calculation method that aggregates summary statistics from normal and anomalous… read more here.
Keywords: detection; enhanced federated; anomaly detection; detection autoencoders ... See more keywords
Comments on “Privacy-Enhanced Federated Learning Against Poisoning Adversaries”
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2023.3238544
Abstract: Liu et al. (2021) recently proposed a privacy-enhanced framework named PEFL to efficiently detect poisoning behaviours in Federated Learning (FL) using homomorphic encryption. In this article, we show that PEFL does not preserve privacy. In… read more here.
Keywords: comments privacy; enhanced federated; federated learning; learning poisoning ... See more keywords
DEEP-FEL: Decentralized, Efficient and Privacy-Enhanced Federated Edge Learning for Healthcare Cyber Physical Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2022.3175945
Abstract: The rapid development of Internet of Things (IoT) stimulates the innovation for the health-related devices such as remote patient monitoring, connected inhalers and ingestible sensors. Simultaneously, with the aid of numerous equipments, a great number… read more here.
Keywords: enhanced federated; federated edge; efficient privacy; privacy enhanced ... See more keywords