Sep 3, 2024 · We propose a DDoS attack detection scheme based on centralized federated learning, where multiple participating nodes locally train models and upload them to a ...

In this paper, we propose two DDoS attack detection schemes based on federated learning techniques for defending against DDoS attacks in the blockchain.

Sep 3, 2024 · We present a new DDoS attack detection algorithm based on traffic variations and design two machine learning models for DDoS identification and ...

Dec 9, 2024 · This study introduces a Federated Learning-based approach, named Federated Learning for Decentralized DDoS Attack Detection (FL-DAD), which utilizes ...

In this paper, we propose a novel adaptive Federated. Learning Approach to DDoS attack detection (FLAD), in which the server verifies the classification ...

Federated learning is used at the federated layer for privacy preservation to mitigate the negative impacts required for fast processing, accuracy, stability, ...

In cloud-based environments, this approach is intended to detect cyberattacks while upholding users' constitutionally protected rights to personal privacy.

We propose a trusted multi-domain DDoS detection method based on federated learning. Firstly, we divide the types of DDoS attacks into different sub-attacks.

This article proposes a new approach to threat intelligence sharing called BFLS (Blockchain and Federated Learning for sharing threat detection models as Cyber ...

Oct 17, 2024 · This study introduces a federated learning model designed to detect DDoS attacks in heterogeneous IoT environments. The research entails ...