A reinforcement learning attacker manipulates client sensor observations in federated learning to induce repetitive server memory updates, achieving around 70% repeated update rate and enabling remote Rowhammer bit flips on an automatic speech recognition model.
Are we susceptible to rowhammer? an end-to-end method- ology for cloud providers
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Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients
A reinforcement learning attacker manipulates client sensor observations in federated learning to induce repetitive server memory updates, achieving around 70% repeated update rate and enabling remote Rowhammer bit flips on an automatic speech recognition model.