1 citations · 1 across the 4 of their papers we have counts for
4 papers
SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark
Rui Wen, Yiyong Liu, Michael Backes +1
Data reconstruction attacks, which aim to recover the training dataset of a target model with limited access, have gained increasing attention in recent years. However, there is cu…
Efficient Data-Free Model Stealing with Label Diversity
Yiyong Liu, Rui Wen, Michael Backes +1
Machine learning as a Service (MLaaS) allows users to query the machine learning model in an API manner, which provides an opportunity for users to enjoy the benefits brought by th…
Membership Inference Attacks by Exploiting Loss Trajectory
Yiyong Liu, Zhengyu Zhao, Michael Backes +1
Machine learning models are vulnerable to membership inference attacks in which an adversary aims to predict whether or not a particular sample was contained in the target model's…
Auditing Membership Leakages of Multi-Exit Networks
Zheng Li, Yiyong Liu, Xinlei He +3
Relying on the fact that not all inputs require the same amount of computation to yield a confident prediction, multi-exit networks are gaining attention as a prominent approach fo…