5 citations · 7 across the 4 of their papers we have counts for
5 papers
Momentum Gradient Descent Federated Learning with Local Differential Privacy
Mengde Han, Tianqing Zhu, Wanlei Zhou
Nowadays, the development of information technology is growing rapidly. In the big data era, the privacy of personal information has been more pronounced. The major challenge is to…
One Parameter Defense -- Defending against Data Inference Attacks via Differential Privacy
Dayong Ye, Sheng Shen, Tianqing Zhu +2
Machine learning models are vulnerable to data inference attacks, such as membership inference and model inversion attacks. In these types of breaches, an adversary attempts to inf…
Model Inversion Attack against Transfer Learning: Inverting a Model without Accessing It
Dayong Ye, Huiqiang Chen, Shuai Zhou +3
Transfer learning is an important approach that produces pre-trained teacher models which can be used to quickly build specialized student models. However, recent research on trans…
Label-only Model Inversion Attack: The Attack that Requires the Least Information
Dayong Ye, Tianqing Zhu, Shuai Zhou +2
In a model inversion attack, an adversary attempts to reconstruct the data records, used to train a target model, using only the model's output. In launching a contemporary model i…
Can Steering Wheel Detect Your Driving Fatigue?
Jianchao Lu, Xi Zheng, Tianyi Zhang +5
Automated Driving System (ADS) has attracted increasing attention from both industrial and academic communities due to its potential for increasing the safety, mobility and efficie…