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Measuring Lower Bounds of Local Differential Privacy via Adversary
  Instantiations in Federated Learning

Measuring Lower Bounds of Local Differential Privacy via Adversary Instantiations in Federated Learning

18 June 2022
Marin Matsumoto
Tsubasa Takahashi
Seng Pei Liew
M. Oguchi
    FedML
    BDL
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Papers citing "Measuring Lower Bounds of Local Differential Privacy via Adversary Instantiations in Federated Learning"

2 / 2 papers shown
Title
Amplification by Shuffling: From Local to Central Differential Privacy
  via Anonymity
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
Ulfar Erlingsson
Vitaly Feldman
Ilya Mironov
A. Raghunathan
Kunal Talwar
Abhradeep Thakurta
138
420
0
29 Nov 2018
Prochlo: Strong Privacy for Analytics in the Crowd
Prochlo: Strong Privacy for Analytics in the Crowd
Andrea Bittau
Ulfar Erlingsson
Petros Maniatis
Ilya Mironov
A. Raghunathan
David Lie
Mitch Rudominer
Ushasree Kode
J. Tinnés
B. Seefeld
85
278
0
02 Oct 2017
1