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Low-Cost High-Power Membership Inference Attacks

Low-Cost High-Power Membership Inference Attacks

6 December 2023
Sajjad Zarifzadeh
Philippe Liu
Reza Shokri
ArXivPDFHTML

Papers citing "Low-Cost High-Power Membership Inference Attacks"

13 / 13 papers shown
Title
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Sonal Allana
Mohan Kankanhalli
Rozita Dara
32
0
0
05 May 2025
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
Jiamin Chang
Yiming Li
Hammond Pearce
Ruoxi Sun
Bo-wen Li
Minhui Xue
40
0
0
28 Apr 2025
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics
Yifeng Mao
Bozhidar Stevanoski
Yves-Alexandre de Montjoye
52
0
0
25 Apr 2025
AMUN: Adversarial Machine UNlearning
AMUN: Adversarial Machine UNlearning
A. Boroojeny
Hari Sundaram
Varun Chandrasekaran
MU
AAML
48
0
0
02 Mar 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study
Ayana Moshruba
Ihsen Alouani
Maryam Parsa
AAML
54
3
0
24 Feb 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus
Lukas Wutschitz
Santiago Zanella Béguelin
Shruti Tople
Reza Shokri
82
0
0
24 Feb 2025
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
Junyi Guan
Abhijith Sharma
Chong Tian
Salem Lahlou
AAML
49
1
0
18 Feb 2025
On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy
On the Implicit Relation Between Low-Rank Adaptation and Differential Privacy
Saber Malekmohammadi
G. Farnadi
32
2
0
26 Sep 2024
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
Cheng Wang
Yiwei Wang
Bryan Hooi
Yujun Cai
Nanyun Peng
Kai-Wei Chang
42
3
0
05 Sep 2024
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language
  Models for Privacy Leakage
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage
Md. Rafi Ur Rashid
Jing Liu
T. Koike-Akino
Shagufta Mehnaz
Ye Wang
MU
SILM
46
3
0
30 Aug 2024
Label Smoothing Improves Machine Unlearning
Label Smoothing Improves Machine Unlearning
Zonglin Di
Zhaowei Zhu
Jinghan Jia
Jiancheng Liu
Zafar Takhirov
Bo Jiang
Yuanshun Yao
Sijia Liu
Yang Liu
40
2
0
11 Jun 2024
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
290
1,831
0
14 Dec 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models
Systematic Evaluation of Privacy Risks of Machine Learning Models
Liwei Song
Prateek Mittal
MIACV
196
359
0
24 Mar 2020
1