6 papers
Harnessing Sparsification in Federated Learning: A Secure, Efficient, and Differentially Private Realization
Shuangqing Xu, Yifeng Zheng, Zhongyun Hua
Federated learning (FL) enables multiple clients to jointly train a model by sharing only gradient updates for aggregation instead of raw data. Due to the transmission of very high…
Lightweight Joint Audio-Visual Deepfake Detection via Single-Stream Multi-Modal Learning Framework
Kuiyuan Zhang, Wenjie Pei, Rushi Lan +2
Deepfakes are AI-synthesized multimedia data that may be abused for spreading misinformation. Deepfake generation involves both visual and audio manipulation. To detect audio-visua…
Reversible Data Hiding over Encrypted Images via Intrinsic Correlation in Block-Based Secret Sharing
Jianhui Zou, Weijia Cao, Shuang Yi +2
With the rapid advancements in information technology, reversible data hiding over encrypted images (RDH-EI) has become essential for secure image management in cloud services. How…
Phoneme-Level Feature Discrepancies: A Key to Detecting Sophisticated Speech Deepfakes
Kuiyuan Zhang, Zhongyun Hua, Rushi Lan +2
Recent advancements in text-to-speech and speech conversion technologies have enabled the creation of highly convincing synthetic speech. While these innovations offer numerous pra…
Robust AI-Synthesized Speech Detection Using Feature Decomposition Learning and Synthesizer Feature Augmentation
Kuiyuan Zhang, Zhongyun Hua, Yushu Zhang +2
AI-synthesized speech, also known as deepfake speech, has recently raised significant concerns due to the rapid advancement of speech synthesis and speech conversion techniques. Pr…
Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy
Shuangqing Xu, Yifeng Zheng, Zhongyun Hua
Federated learning (FL) has rapidly become a compelling paradigm that enables multiple clients to jointly train a model by sharing only gradient updates for aggregation, without re…