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Pool Inference Attacks on Local Differential Privacy: Quantifying the
  Privacy Guarantees of Apple's Count Mean Sketch in Practice

Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple's Count Mean Sketch in Practice

14 April 2023
Andrea Gadotti
Frederick Sell
Reethika Ramesh
Jinyuan Jia
ArXivPDFHTML

Papers citing "Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple's Count Mean Sketch in Practice"

11 / 11 papers shown
Title
DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy
DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy
Nicolas Küchler
Alexander Viand
Hidde Lycklama
Anwar Hithnawi
26
0
0
10 May 2025
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
Héber H. Arcolezi
Sébastien Gambs
AAML
48
0
0
03 Mar 2025
Adanonymizer: Interactively Navigating and Balancing the Duality of
  Privacy and Output Performance in Human-LLM Interaction
Adanonymizer: Interactively Navigating and Balancing the Duality of Privacy and Output Performance in Human-LLM Interaction
Shuning Zhang
Xin Yi
Haobin Xing
Lyumanshan Ye
Yongquan Hu
Hewu Li
29
2
0
19 Oct 2024
Correction to Local Information Privacy and Its Applications to Data
  Aggregation
Correction to Local Information Privacy and Its Applications to Data Aggregation
Bo Jiang
Ming Li
Ravi Tandon
27
0
0
16 Oct 2024
Nearly Tight Black-Box Auditing of Differentially Private Machine
  Learning
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning
Meenatchi Sundaram Muthu Selva Annamalai
Emiliano De Cristofaro
25
11
0
23 May 2024
"What do you want from theory alone?" Experimenting with Tight Auditing
  of Differentially Private Synthetic Data Generation
"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation
Meenatchi Sundaram Muthu Selva Annamalai
Georgi Ganev
Emiliano De Cristofaro
35
9
0
16 May 2024
Revealing the True Cost of Locally Differentially Private Protocols: An
  Auditing Perspective
Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
Héber H. Arcolezi
Sébastien Gambs
30
1
0
04 Sep 2023
Transparency in App Analytics: Analyzing the Collection of User
  Interaction Data
Transparency in App Analytics: Analyzing the Collection of User Interaction Data
Feiyang Tang
Bjarte M. Østvold
11
1
0
20 Jun 2023
A Linear Reconstruction Approach for Attribute Inference Attacks against
  Synthetic Data
A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data
Meenatchi Sundaram Muthu Selva Annamalai
Andrea Gadotti
Luc Rocher
MIACV
16
21
0
24 Jan 2023
On the Risks of Collecting Multidimensional Data Under Local
  Differential Privacy
On the Risks of Collecting Multidimensional Data Under Local Differential Privacy
Héber H. Arcolezi
Sébastien Gambs
Jean-François Couchot
C. Palamidessi
21
12
0
04 Sep 2022
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
79
278
0
02 Oct 2017
1