3 papers
cs.DC2026
Model-Consistent Byzantine-Resilient Decentralized Federated Learning for Collaborative Missions
Yue Li, Sudip Bhujel, Cameron Lira +2
Decentralized federated learning (DFL) is a promising paradigm for autonomous nodes to collaboratively train AI models without relying on a central server. However, existing DFL so…
cs.LG2024
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning
Zhengyuan Jiang, Xingyu Lyu, Shanghao Shi +5
Federated learning, while being a promising approach for collaborative model training, is susceptible to backdoor attacks due to its decentralized nature. Backdoor attacks have sho…
cs.LG2024
Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks
Md Hasan Shahriar, Ning Wang, Naren Ramakrishnan +2
The exponential adoption of machine learning (ML) is propelling the world into a future of distributed and intelligent automation and data-driven solutions. However, the proliferat…