most citedLocate and Verify: A Two-Stream Network for Improved Deepfake Detection

2 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2024

ALIF: Low-Cost Adversarial Audio Attacks on Black-Box Speech Platforms using Linguistic Features

Peng Cheng, Yuwei Wang, Peng Huang +5

Extensive research has revealed that adversarial examples (AE) pose a significant threat to voice-controllable smart devices. Recent studies have proposed black-box adversarial att…

cs.CR20242 cited

Releasing Malevolence from Benevolence: The Menace of Benign Data on Machine Unlearning

Binhao Ma, Tianhang Zheng, Hongsheng Hu +5

Machine learning models trained on vast amounts of real or synthetic data often achieve outstanding predictive performance across various domains. However, this utility comes with…

cs.CV2024

Do As I Do: Pose Guided Human Motion Copy

Sifan Wu, Zhenguang Liu, Beibei Zhang +4

Human motion copy is an intriguing yet challenging task in artificial intelligence and computer vision, which strives to generate a fake video of a target person performing the mot…

cs.CV2024

Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection

Zhongjie Ba, Qingyu Liu, Zhenguang Liu +4

Deepfake technology has given rise to a spectrum of novel and compelling applications. Unfortunately, the widespread proliferation of high-fidelity fake videos has led to pervasive…

cs.CR2024

Phoneme-Based Proactive Anti-Eavesdropping with Controlled Recording Privilege

Peng Huang, Yao Wei, Peng Cheng +5

The widespread smart devices raise people's concerns of being eavesdropped on. To enhance voice privacy, recent studies exploit the nonlinearity in microphone to jam audio recorder…

cs.CR20231 cited

FLTracer: Accurate Poisoning Attack Provenance in Federated Learning

Xinyu Zhang, Qingyu Liu, Zhongjie Ba +5

Federated Learning (FL) is a promising distributed learning approach that enables multiple clients to collaboratively train a shared global model. However, recent studies show that…