Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
-
Updated
Nov 15, 2017 - Python
Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
This repository contains personal notes and summaries on Secure and Private AI
Differential Privacy Protection against MembershipInference Attack on Machine Learning for Genomic Data
Testing membership inference attacks on Deep learning models (LSTM, CNN);
Implementations on Security and Privacy in ML; Evasion Attack, Model Stealing, Model Poisoning, Membership Inference Attacks, ...
Membership inference against Federated learning.
The source code for ICML2021 paper When Does Data Augmentation Help With Membership Inference Attacks?
Universität des Saarlandes - Privacy Enhancing Technologies 2021 - Semester Project
DP-UTIL: A Comprehensive Utility Analysis of Differential Privacy in Machine Learning
Accompanying code for "Disparate Vulnerability to Membership Inference Attacks"
Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
Defending Privacy Against More Knowledgeable Membership Inference Attackers
reveal the vulnerabilities of SplitNN
An implementation of ICLR 22 paper "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" in PyTorch
An implementation of loss thresholding attack to infer membership status as described in paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting" (CSF 18) in PyTorch.
Source code for our IJCAI-ECAI 2022 paper "To Trust or Not To Trust Prediction Scores for Membership Inference Attacks"
🔒 Implementation of Shokri et al(2016) "Membership Inference Attacks against Machine Learning Models"
Evaluating the impact of entropy, maximum posterior probability, and standard deviation of probability vector in mitigating black-box membership inference attack
Bachelor's Thesis on Membership Inference Attacks
A mitigation method against privacy violation attacks on face recognition systems
Add a description, image, and links to the membership-inference-attack topic page so that developers can more easily learn about it.
To associate your repository with the membership-inference-attack topic, visit your repo's landing page and select "manage topics."