Poisoning Attacks and Defenses in Federated Learning: A Survey

Autor:	Sagar, Subhash, Li, Chang-Sun, Loke, Seng W., Choi, Jinho
Rok vydání:	2023
Předmět:	Computer Science - Cryptography and Security Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Federated learning (FL) enables the training of models among distributed clients without compromising the privacy of training datasets, while the invisibility of clients datasets and the training process poses a variety of security threats. This survey provides the taxonomy of poisoning attacks and experimental evaluation to discuss the need for robust FL.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2301.05795 Zobrazit plný text záznamu View this record from Arxiv