FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT

The rapid development of Large Language Models (LLMs) has been pivotal in advancing AI, with pre-trained LLMs being adaptable to diverse downstream tasks through fine-tuning. Federated learning (FL) further enhances fine-tuning in a privacy-aware manner by utilizing clients'…

Federated learning, a pioneering paradigm, enables collaborative model training without exposing users’ data to central servers. Most existing federated learning systems necessitate uniform model structures across all clients, restricting their practicality. Several methods …

With increasing privacy concerns in artificial intelligence, regulations have mandated the right to be forgotten, granting individuals the right to withdraw their data from models. Machine unlearning has emerged as a potential solution to enable selective forgetting in model…