chain dynamics. To address these challenges, we propose a novel approach that integrates Federated Learning (FL) and Graph …

collaborative model training. In response, this paper introduces the FED-SPFD model, an innovative federated learning framework … fraud detection systems capable of real-time anomaly interception to safeguard financial activities. While federated … learning frameworks have been employed to address data privacy concerns in financial applications, existing approaches often …

Federated Learning (FL) is an innovative technique that allows multiple firms to collaborate in training machine …

In this paper, we present an adaptive and energy-efficient differentially private federated learning model for IDS in …

infrastructure for decentralized AI applications. This study investigates how decentralized AI techniques, particularly federated … learning, can support joint risk management processes in enterprise networks. First, a comprehensive review of decentralized AI … through a technical prototype, combining architectural design with empirical proof-of-concept experiments on federated …

Im Forschungsprojekt FLEIS (Federated Learning Enhancing IT-Security) wurde von 2021 bis 2024 zusammen mit zwei …In the project FLEIS (Federated Learning Enhancing IT Security), research on IT security in human resource management …

Federated Learning method (CWCSGDFL) is introduced. It aims to improve the efficiency of financial distress prediction by … reduces time complexity in financial distress prediction. Stochastic Gradient Gaussian Kernel Federated Learning approach is …