research
∙
06/23/2023
Deconstructing Classifiers: Towards A Data Reconstruction Attack Against Text Classification Models
Natural language processing (NLP) models have become increasingly popula...
share
research
∙
02/01/2023
Analyzing Leakage of Personally Identifiable Information in Language Models
Language Models (LMs) have been shown to leak information about training...
research
∙
06/10/2022
Bayesian Estimation of Differential Privacy
Algorithms such as Differentially Private SGD enable training machine le...
research
∙
02/04/2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
Inference attacks against Machine Learning (ML) models allow adversaries...
research
∙
10/07/2020
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks
Backdoor attack against deep neural networks is currently being profound...
research
∙
10/06/2020
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models
The tremendous progress of autoencoders and generative adversarial netwo...
research
∙
06/01/2020
BadNL: Backdoor Attacks Against NLP Models
Machine learning (ML) has progressed rapidly during the past decade and ...
research
∙
03/07/2020
Dynamic Backdoor Attacks Against Machine Learning Models
Machine learning (ML) has made tremendous progress during the past decad...
research
∙
09/23/2019
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples
In a membership inference attack, an attacker aims to infer whether a da...
research
∙
04/01/2019
Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning
Machine learning (ML) has progressed rapidly during the past decade and ...
research
∙
08/01/2018
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
With the widespread use of machine learning (ML) techniques, ML as a ser...
research
∙
06/04/2018