ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1806.01246
  4. Cited By
ML-Leaks: Model and Data Independent Membership Inference Attacks and
  Defenses on Machine Learning Models

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

4 June 2018
A. Salem
Yang Zhang
Mathias Humbert
Pascal Berrang
Mario Fritz
Michael Backes
    MIACV
    MIALM
ArXivPDFHTML

Papers citing "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"

50 / 465 papers shown
Title
Subject Membership Inference Attacks in Federated Learning
Subject Membership Inference Attacks in Federated Learning
Anshuman Suri
Pallika H. Kanani
Virendra J. Marathe
Daniel W. Peterson
30
25
0
07 Jun 2022
On the Privacy Properties of GAN-generated Samples
On the Privacy Properties of GAN-generated Samples
Zinan Lin
Vyas Sekar
Giulia Fanti
PICV
21
26
0
03 Jun 2022
Dataset Distillation using Neural Feature Regression
Dataset Distillation using Neural Feature Regression
Yongchao Zhou
E. Nezhadarya
Jimmy Ba
DD
FedML
39
149
0
01 Jun 2022
A Blessing of Dimensionality in Membership Inference through
  Regularization
A Blessing of Dimensionality in Membership Inference through Regularization
Jasper Tan
Daniel LeJeune
Blake Mason
Hamid Javadi
Richard G. Baraniuk
32
18
0
27 May 2022
Membership Inference Attack Using Self Influence Functions
Membership Inference Attack Using Self Influence Functions
Gilad Cohen
Raja Giryes
TDI
30
12
0
26 May 2022
BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural
  Networks via Image Quantization and Contrastive Adversarial Learning
BppAttack: Stealthy and Efficient Trojan Attacks against Deep Neural Networks via Image Quantization and Contrastive Adversarial Learning
Zhenting Wang
Juan Zhai
Shiqing Ma
AAML
126
97
0
26 May 2022
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised
  Learning
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning
Yunhao Yang
Parham Gohari
Ufuk Topcu
18
1
0
25 May 2022
Unintended memorisation of unique features in neural networks
Unintended memorisation of unique features in neural networks
J. Hartley
Sotirios A. Tsaftaris
30
1
0
20 May 2022
Collaborative Drug Discovery: Inference-level Data Protection
  Perspective
Collaborative Drug Discovery: Inference-level Data Protection Perspective
Balázs Pejó
Mina Remeli
Adam Arany
M. Galtier
G. Ács
25
3
0
13 May 2022
l-Leaks: Membership Inference Attacks with Logits
l-Leaks: Membership Inference Attacks with Logits
Shuhao Li
Yajie Wang
Yuan-zhang Li
Yu-an Tan
MIACV
MIALM
14
2
0
13 May 2022
Blockchain-based Secure Client Selection in Federated Learning
Blockchain-based Secure Client Selection in Federated Learning
Truc D. T. Nguyen
Phuc Thai
Tre' R. Jeter
Thang N. Dinh
My T. Thai
17
12
0
11 May 2022
Secure & Private Federated Neuroimaging
Secure & Private Federated Neuroimaging
Dimitris Stripelis
Umang Gupta
Hamza Saleem
Nikhil J. Dhinagar
Tanmay Ghai
...
Greg Ver Steeg
Srivatsan Ravi
Muhammad Naveed
Paul M. Thompson
J. Ambite
FedML
OOD
19
2
0
11 May 2022
Cracking White-box DNN Watermarks via Invariant Neuron Transforms
Cracking White-box DNN Watermarks via Invariant Neuron Transforms
Yifan Yan
Xudong Pan
Yining Wang
Mi Zhang
Min Yang
AAML
19
14
0
30 Apr 2022
A Differentially Private Framework for Deep Learning with Convexified
  Loss Functions
A Differentially Private Framework for Deep Learning with Convexified Loss Functions
Zhigang Lu
Hassan Jameel Asghar
M. Kâafar
Darren Webb
Peter Dickinson
57
15
0
03 Apr 2022
Perfectly Accurate Membership Inference by a Dishonest Central Server in
  Federated Learning
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning
Georg Pichler
Marco Romanelli
L. Rey Vega
Pablo Piantanida
FedML
28
10
0
30 Mar 2022
Leveraging Adversarial Examples to Quantify Membership Information
  Leakage
Leveraging Adversarial Examples to Quantify Membership Information Leakage
Ganesh Del Grosso
Hamid Jalalzai
Georg Pichler
C. Palamidessi
Pablo Piantanida
MIACV
29
21
0
17 Mar 2022
One Parameter Defense -- Defending against Data Inference Attacks via
  Differential Privacy
One Parameter Defense -- Defending against Data Inference Attacks via Differential Privacy
Dayong Ye
Sheng Shen
Tianqing Zhu
B. Liu
Wanlei Zhou
MIACV
16
61
0
13 Mar 2022
Model Inversion Attack against Transfer Learning: Inverting a Model
  without Accessing It
Model Inversion Attack against Transfer Learning: Inverting a Model without Accessing It
Dayong Ye
Huiqiang Chen
Shuai Zhou
Tianqing Zhu
Wanlei Zhou
S. Ji
MIACV
20
6
0
13 Mar 2022
Label-only Model Inversion Attack: The Attack that Requires the Least
  Information
Label-only Model Inversion Attack: The Attack that Requires the Least Information
Dayong Ye
Tianqing Zhu
Shuai Zhou
B. Liu
Wanlei Zhou
22
4
0
13 Mar 2022
Membership Privacy Protection for Image Translation Models via
  Adversarial Knowledge Distillation
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation
Saeed Ranjbar Alvar
Lanjun Wang
Jiangbo Pei
Yong Zhang
VLM
16
2
0
10 Mar 2022
Quantifying Privacy Risks of Masked Language Models Using Membership
  Inference Attacks
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks
Fatemehsadat Mireshghallah
Kartik Goyal
Archit Uniyal
Taylor Berg-Kirkpatrick
Reza Shokri
MIALM
32
151
0
08 Mar 2022
Training privacy-preserving video analytics pipelines by suppressing
  features that reveal information about private attributes
Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributes
C. Li
Andrea Cavallaro
PICV
14
0
0
05 Mar 2022
User-Level Membership Inference Attack against Metric Embedding Learning
User-Level Membership Inference Attack against Metric Embedding Learning
Guoyao Li
Shahbaz Rezaei
Xin Liu
18
23
0
04 Mar 2022
MIAShield: Defending Membership Inference Attacks via Preemptive
  Exclusion of Members
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members
Ismat Jarin
Birhanu Eshete
26
9
0
02 Mar 2022
Bounding Membership Inference
Bounding Membership Inference
Anvith Thudi
Ilia Shumailov
Franziska Boenisch
Nicolas Papernot
27
18
0
24 Feb 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey
M. A. Ramírez
Song-Kyoo Kim
H. A. Hamadi
Ernesto Damiani
Young-Ji Byon
Tae-Yeon Kim
C. Cho
C. Yeun
AAML
17
37
0
21 Feb 2022
Measuring Unintended Memorisation of Unique Private Features in Neural
  Networks
Measuring Unintended Memorisation of Unique Private Features in Neural Networks
J. Hartley
Sotirios A. Tsaftaris
19
7
0
16 Feb 2022
Defending against Reconstruction Attacks with Rényi Differential
  Privacy
Defending against Reconstruction Attacks with Rényi Differential Privacy
Pierre Stock
I. Shilov
Ilya Mironov
Alexandre Sablayrolles
AAML
SILM
MIACV
12
39
0
15 Feb 2022
NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data
  Release
NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data Release
Donghao Li
Yang Cao
Yuan Yao
35
2
0
14 Feb 2022
What Does it Mean for a Language Model to Preserve Privacy?
What Does it Mean for a Language Model to Preserve Privacy?
Hannah Brown
Katherine Lee
Fatemehsadat Mireshghallah
Reza Shokri
Florian Tramèr
PILM
31
232
0
11 Feb 2022
Privacy-preserving Generative Framework Against Membership Inference
  Attacks
Privacy-preserving Generative Framework Against Membership Inference Attacks
Ruikang Yang
Jianfeng Ma
Yinbin Miao
Xindi Ma
19
5
0
11 Feb 2022
PPA: Preference Profiling Attack Against Federated Learning
PPA: Preference Profiling Attack Against Federated Learning
Chunyi Zhou
Yansong Gao
Anmin Fu
Kai Chen
Zhiyang Dai
Zhi-Li Zhang
Minhui Xue
Yuqing Zhang
AAML
25
21
0
10 Feb 2022
Deletion Inference, Reconstruction, and Compliance in Machine
  (Un)Learning
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning
Ji Gao
Sanjam Garg
Mohammad Mahmoody
Prashant Nalini Vasudevan
MIACV
AAML
19
22
0
07 Feb 2022
Membership Inference Attacks and Defenses in Neural Network Pruning
Membership Inference Attacks and Defenses in Neural Network Pruning
Xiaoyong Yuan
Lan Zhang
AAML
16
44
0
07 Feb 2022
Redactor: A Data-centric and Individualized Defense Against Inference
  Attacks
Redactor: A Data-centric and Individualized Defense Against Inference Attacks
Geon Heo
Steven Euijong Whang
AAML
17
2
0
07 Feb 2022
Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks
Jan Aalmoes
Vasisht Duddu
A. Boutet
21
10
0
04 Feb 2022
Parameters or Privacy: A Provable Tradeoff Between Overparameterization
  and Membership Inference
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference
Jasper Tan
Blake Mason
Hamid Javadi
Richard G. Baraniuk
FedML
37
19
0
02 Feb 2022
Bounding Training Data Reconstruction in Private (Deep) Learning
Bounding Training Data Reconstruction in Private (Deep) Learning
Chuan Guo
Brian Karrer
Kamalika Chaudhuri
L. V. D. van der Maaten
115
53
0
28 Jan 2022
SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained
  Encoders
SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained Encoders
Tianshuo Cong
Xinlei He
Yang Zhang
21
52
0
27 Jan 2022
Federated Unlearning with Knowledge Distillation
Federated Unlearning with Knowledge Distillation
Chen Wu
Sencun Zhu
P. Mitra
MU
10
107
0
24 Jan 2022
FedComm: Federated Learning as a Medium for Covert Communication
FedComm: Federated Learning as a Medium for Covert Communication
Dorjan Hitaj
Giulio Pagnotta
Briland Hitaj
Fernando Perez-Cruz
L. Mancini
FedML
32
10
0
21 Jan 2022
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image
  Encoders
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders
Zeyang Sha
Xinlei He
Ning Yu
Michael Backes
Yang Zhang
25
34
0
19 Jan 2022
Zero-Shot Machine Unlearning
Zero-Shot Machine Unlearning
Vikram S Chundawat
Ayush K Tarun
Murari Mandal
Mohan S. Kankanhalli
MU
19
120
0
14 Jan 2022
Reconstructing Training Data with Informed Adversaries
Reconstructing Training Data with Informed Adversaries
Borja Balle
Giovanni Cherubin
Jamie Hayes
MIACV
AAML
43
158
0
13 Jan 2022
Security for Machine Learning-based Software Systems: a survey of
  threats, practices and challenges
Security for Machine Learning-based Software Systems: a survey of threats, practices and challenges
Huaming Chen
Muhammad Ali Babar
AAML
34
21
0
12 Jan 2022
Gradient Leakage Attack Resilient Deep Learning
Gradient Leakage Attack Resilient Deep Learning
Wenqi Wei
Ling Liu
SILM
PILM
AAML
27
46
0
25 Dec 2021
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive
  Survey
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey
Shangwei Guo
Xu Zhang
Feiyu Yang
Tianwei Zhang
Yan Gan
Tao Xiang
Yang Liu
FedML
31
9
0
19 Dec 2021
Correlation inference attacks against machine learning models
Correlation inference attacks against machine learning models
Ana-Maria Creţu
Florent Guépin
Yves-Alexandre de Montjoye
MIACV
AAML
38
5
0
16 Dec 2021
Model Stealing Attacks Against Inductive Graph Neural Networks
Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen
Xinlei He
Yufei Han
Yang Zhang
19
60
0
15 Dec 2021
SoK: Anti-Facial Recognition Technology
SoK: Anti-Facial Recognition Technology
Emily Wenger
Shawn Shan
Haitao Zheng
Ben Y. Zhao
PICV
32
13
0
08 Dec 2021
Previous
123...1056789
Next