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Home / Papers / A Taxonomy of Attacks on Federated Learning

A Taxonomy of Attacks on Federated Learning

DOI: 10.1109/msec.2020.3039941Source
197 Citations•2020•
Malhar Jere, Tyler Farnan, Farinaz Koushanfar
IEEE Security & Privacy

A taxonomy of recent attacks on federated learning systems is provided and the need for more robust threat modeling in Federated learning environments is detailed.

Abstract

Federated learning is a privacy-by-design framework that enables training deep neural networks from decentralized sources of data, but it is fraught with innumerable attack surfaces. We provide a taxonomy of recent attacks on federated learning systems and detail the need for more robust threat modeling in federated learning environments.