Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2025.3629864
Abstract: Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learning (DFL) extends the FL paradigm by eliminating the central server, thereby… read more here.
Keywords: robust aggregation; byzantine; federated learning; byzantine robust ... See more keywords
Collusive Backdoor Attacks in Federated Learning Frameworks for IoT Systems
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3368754
Abstract: Internet of Things (IoT) devices generate massive amounts of data from local devices, making federated learning (FL) a viable distributed machine learning paradigm to learn a global model while keeping private data locally in various… read more here.
Keywords: backdoor; backdoor attacks; iot systems; collusive backdoor ... See more keywords
A robust aggregation operators for multi-criteria decision-making with intuitionistic fuzzy soft set environment
Sign Up to like & getrecommendations! Published in 2017 at "Scientia Iranica"
DOI: 10.24200/sci.2017.4433
Abstract: Soft set theory acts as a fundamental tool for handling the uncertainty in the data by adding aparameterized factor during the process as compared to fuzzy as well as intuitionistic fuzzy settheory. In this manuscript,… read more here.
Keywords: robust aggregation; intuitionistic fuzzy; operators multi; aggregation operators ... See more keywords
Robust Aggregation for Federated Learning by Minimum γ-Divergence Estimation
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24050686
Abstract: Federated learning is a framework for multiple devices or institutions, called local clients, to collaboratively train a global model without sharing their data. For federated learning with a central server, an aggregation algorithm integrates model… read more here.
Keywords: aggregation; robust aggregation; federated learning; divergence estimation ... See more keywords