15 citations · 38 across the 6 of their papers we have counts for
22 papers
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…
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…
TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing
Aoting Hu, Renjie Xie, Zhigang Lu +2
Generative Adversarial Networks (GAN)-synthesized table publishing lets people privately learn insights without access to the private table. However, existing studies on Membership…
Dissecting Click Fraud Autonomy in the Wild
Tong Zhu, Yan Meng, Haotian Hu +3
Although the use of pay-per-click mechanisms stimulates the prosperity of the mobile advertisement network, fraudulent ad clicks result in huge financial losses for advertisers. Ex…
Hidden Backdoors in Human-Centric Language Models
Shaofeng Li, Hui Liu, Tian Dong +4
Natural language processing (NLP) systems have been proven to be vulnerable to backdoor attacks, whereby hidden features (backdoors) are trained into a language model and may only…
Explainability-based Backdoor Attacks Against Graph Neural Networks
Jing Xu, Minhui, Xue +1
Backdoor attacks represent a serious threat to neural network models. A backdoored model will misclassify the trigger-embedded inputs into an attacker-chosen target label while per…