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$k$-Anonymity in Practice: How Generalisation and Suppression Affect
  Machine Learning Classifiers
v1v2 (latest)

kkk-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers

Computers & security (CS), 2021
9 February 2021
D. Slijepcevic
Maximilian Henzl
Lukas Daniel Klausner
Tobias Dam
Peter Kieseberg
Matthias Zeppelzauer
ArXiv (abs)PDFHTML

Papers citing "$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers"

13 / 13 papers shown
ALPINE: Closed-Loop Adaptive Privacy Budget Allocation for Mobile Edge Crowdsensing
ALPINE: Closed-Loop Adaptive Privacy Budget Allocation for Mobile Edge Crowdsensing
Guanjie Cheng
Siyang Liu
Junqin Huang
Xinkui Zhao
Yin Wang
Mengying Zhu
Linghe Kong
166
1
0
10 Apr 2026
AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders
AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders
Hiroya Kato
Kentaro Kita
Kento Hasegawa
Seira Hidano
133
0
0
12 Aug 2025
Multi-Objective Optimization-Based Anonymization of Structured Data for Machine Learning Application
Multi-Objective Optimization-Based Anonymization of Structured Data for Machine Learning Application
Yusi Wei
Hande Y. Benson
Joseph K. Agor
Muge Capan
199
2
0
02 Jan 2025
Intermediate Outputs Are More Sensitive Than You Think
Intermediate Outputs Are More Sensitive Than You Think
Tao Huang
Qingyu Huang
Jiayang Meng
AAML
346
1
0
01 Dec 2024
Enabling Humanitarian Applications with Targeted Differential Privacy
Enabling Humanitarian Applications with Targeted Differential Privacy
Nitin Kohli
J. Blumenstock
282
0
0
24 Aug 2024
Synthetic Data: Revisiting the Privacy-Utility Trade-off
Synthetic Data: Revisiting the Privacy-Utility Trade-off
Fatima Jahan Sarmin
Atiquer Rahman Sarkar
Yang Wang
Noman Mohammed
363
19
0
09 Jul 2024
Delete My Account: Impact of Data Deletion on Machine Learning
  Classifiers
Delete My Account: Impact of Data Deletion on Machine Learning Classifiers
Tobias Dam
Maximilian Henzl
Lukas Daniel Klausner
121
1
0
17 Nov 2023
Privacy-Preserving Taxi-Demand Prediction Using Federated Learning
Privacy-Preserving Taxi-Demand Prediction Using Federated LearningInternational Conference on Smart Computing (SMARTCOMP), 2023
Yumeki Goto
Tomoya Matsumoto
Hamada Rizk
Naoto Yanai
Hirozumi Yamaguchi
230
10
0
14 May 2023
Comparison of machine learning models applied on anonymized data with
  different techniques
Comparison of machine learning models applied on anonymized data with different techniquesComputer Science Symposium in Russia (CSR), 2023
Judith Sáinz-Pardo Díaz
Á. García
319
9
0
12 May 2023
Energy cost and machine learning accuracy impact of k-anonymisation and
  synthetic data techniques
Energy cost and machine learning accuracy impact of k-anonymisation and synthetic data techniquesICT for Sustainability (ICT4S), 2023
Pepijn de Reus
Ana Oprescu
Koen van Elsen
161
6
0
11 May 2023
Anonymous Bandits for Multi-User Systems
Anonymous Bandits for Multi-User SystemsNeural Information Processing Systems (NeurIPS), 2022
Hossein Esfandiari
Vahab Mirrokni
Jon Schneider
PICV
182
2
0
21 Oct 2022
The privacy issue of counterfactual explanations: explanation linkage
  attacks
The privacy issue of counterfactual explanations: explanation linkage attacksACM Transactions on Intelligent Systems and Technology (ACM TIST), 2022
S. Goethals
Kenneth Sörensen
David Martens
168
37
0
21 Oct 2022
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing
HyObscure: Hybrid Obscuring for Privacy-Preserving Data Publishing
Xiao Han
Yuncong Yang
Junjie Wu
201
4
0
15 Dec 2021
1
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