183 citations · 220 across the 10 of their papers we have counts for
4 papers · 1 filter
New Challenges in Reinforcement Learning: A Survey of Security and Privacy
Yunjiao Lei, Dayong Ye, Sheng Shen +3
Reinforcement learning (RL) is one of the most important branches of AI. Due to its capacity for self-adaption and decision-making in dynamic environments, reinforcement learning h…
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…