300 citations · 1.6k across the 40 of their papers we have counts for
7 papers · 2 filters
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models
Ahmed Salem, Yannick Sautter, Michael Backes +2
The tremendous progress of autoencoders and generative adversarial networks (GANs) has led to their application to multiple critical tasks, such as fraud detection and sanitized da…
Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks
Ahmed Salem, Michael Backes, Yang Zhang
Backdoor attack against deep neural networks is currently being profoundly investigated due to its severe security consequences. Current state-of-the-art backdoor attacks require t…
Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning
Yang Zou, Zhikun Zhang, Michael Backes +1
While being deployed in many critical applications as core components, machine learning (ML) models are vulnerable to various security and privacy attacks. One major privacy attack…
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements
Xiaoyi Chen, Ahmed Salem, Dingfan Chen +5
Deep neural networks (DNNs) have progressed rapidly during the past decade and have been deployed in various real-world applications. Meanwhile, DNN models have been shown to be vu…
When Machine Unlearning Jeopardizes Privacy
Min Chen, Zhikun Zhang, Tianhao Wang +3
The right to be forgotten states that a data owner has the right to erase their data from an entity storing it. In the context of machine learning (ML), the right to be forgotten r…
Stealing Links from Graph Neural Networks
Xinlei He, Jinyuan Jia, Michael Backes +2
Graph data, such as chemical networks and social networks, may be deemed confidential/private because the data owner often spends lots of resources collecting the data or the data…
Dynamic Backdoor Attacks Against Machine Learning Models
Ahmed Salem, Rui Wen, Michael Backes +2
Machine learning (ML) has made tremendous progress during the past decade and is being adopted in various critical real-world applications. However, recent research has shown that…