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Atul Sharma

2 accepted papers

2024

Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning

CVPR 2024poster

Federated learning is a decentralized learning paradigm introduced to preserve privacy of client data. Despite this prior work has shown that an attacker at the server can still reconstruct the private training data using only the client updates. These attacks are known as data reconstruction attack…

Cited by 4SourcePDFScholar
2023

The Resource Problem of Using Linear Layer Leakage Attack in Federated Learning

CVPR 2023poster

Secure aggregation promises a heightened level of privacy in federated learning, maintaining that a server only has access to a decrypted aggregate update. Within this setting, linear layer leakage methods are the only data reconstruction attacks able to scale and achieve a high leakage rate regardl…

Cited by 18SourcePDFScholar