591 citations · 1k across the 37 of their papers we have counts for
6 papers · 1 filter
M^4I: Multi-modal Models Membership Inference
Pingyi Hu, Zihan Wang, Ruoxi Sun +2
With the development of machine learning techniques, the attention of research has been moved from single-modal learning to multi-modal learning, as real-world data exist in the fo…
The "Beatrix'' Resurrections: Robust Backdoor Detection via Gram Matrices
Wanlun Ma, Derui Wang, Ruoxi Sun +3
Deep Neural Networks (DNNs) are susceptible to backdoor attacks during training. The model corrupted in this way functions normally, but when triggered by certain patterns in the i…
StyleFool: Fooling Video Classification Systems via Style Transfer
Yuxin Cao, Xi Xiao, Ruoxi Sun +3
Video classification systems are vulnerable to adversarial attacks, which can create severe security problems in video verification. Current black-box attacks need a large number o…
PublicCheck: Public Integrity Verification for Services of Run-time Deep Models
Shuo Wang, Sharif Abuadbba, Sidharth Agarwal +6
Existing integrity verification approaches for deep models are designed for private verification (i.e., assuming the service provider is honest, with white-box access to model para…
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations
Zirui Peng, Shaofeng Li, Guoxing Chen +3
In this paper, we propose a novel and practical mechanism which enables the service provider to verify whether a suspect model is stolen from the victim model via model extraction…
PPA: Preference Profiling Attack Against Federated Learning
Chunyi Zhou, Yansong Gao, Anmin Fu +5
Federated learning (FL) trains a global model across a number of decentralized users, each with a local dataset. Compared to traditional centralized learning, FL does not require d…