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cs.CR2026
PhantomSeal: Proactive Deepfakes Defense with Identity/Context Protection and Forensic Tracing
Liangqin Ren, Zeyan Liu, Ye Wang +3
Deepfakes, especially face-swapping attacks, pose significant challenges to authenticity, security, and ethics across science, engineering, and society. While most existing detecti…
cs.CR2026★ 7 cited
PrivDNN: A Secure Multi-Party Computation Framework for Deep Learning using Partial DNN Encryption
Liangqin Ren, Zeyan Liu, Fengjun Li +3
In the past decade, we have witnessed an exponential growth of deep learning models, platforms, and applications. While existing DL applications and Machine Learning as a service (…
cs.CR2022
Hide and Seek: on the Stealthiness of Attacks against Deep Learning Systems
Zeyan Liu, Fengjun Li, Jingqiang Lin +2
With the growing popularity of artificial intelligence and machine learning, a wide spectrum of attacks against deep learning models have been proposed in the literature. Both the…