WebJul 7, 2024 · How to backdoor federated learning. arXiv preprint arXiv:1807.00459, 2024. ... Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, and H. Brendan McMahan. Can you really backdoor federated learning ... WebJul 9, 2024 · Abstract. Due to its decentralized nature, Federated Learning (FL) lends itself to adversarial attacks in the form of backdoors during training. The goal of a backdoor is …

Attack of the tails: yes, you really can backdoor federated learning

WebNov 18, 2024 · This paper focuses on backdoor attacks in the federated learning setting, where the goal of the adversary is to reduce the performance of the model on targeted … WebNov 15, 2024 · Dynamic backdoor attacks against federated learning. Federated Learning (FL) is a new machine learning framework, which enables millions of participants to collaboratively train machine learning model without compromising data privacy and security. Due to the independence and confidentiality of each client, FL does not … tamarind heartwood

Can You Really Backdoor Federated Learning? – Google Research

WebDue to its decentralized nature, Federated Learning (FL) lends itself to adversarial attacks in the form of backdoors during training. The goal of a backdoor is to corrupt the performance of the trained model on specific sub-tasks (e.g., by classifying green cars as frogs).A range of FL backdoor attacks have been introduced in the literature, but also … http://proceedings.mlr.press/v108/bagdasaryan20a/bagdasaryan20a.pdf WebFeb 9, 2024 · The distributed nature and privacy-preserving characteristics of federated learning make it prone to the threat of poisoning attacks, especially backdoor attacks, where the adversary implants backdoors to misguide the … tamarind hill singapore wedding