7 citations · 11 across the 9 of their papers we have counts for
9 papers
Take Fake as Real: Realistic-like Robust Black-box Adversarial Attack to Evade AIGC Detection
Caiyun Xie, Dengpan Ye, Yunming Zhang +4
The security of AI-generated content (AIGC) detection is crucial for ensuring multimedia content credibility. To enhance detector security, research on adversarial attacks has beco…
StyleMark: A Robust Watermarking Method for Art Style Images Against Black-Box Arbitrary Style Transfer
Yunming Zhang, Dengpan Ye, Sipeng Shen +1
Arbitrary Style Transfer (AST) achieves the rendering of real natural images into the painting styles of arbitrary art style images, promoting art communication. However, misuse of…
ErasableMask: A Robust and Erasable Privacy Protection Scheme against Black-box Face Recognition Models
Sipeng Shen, Yunming Zhang, Dengpan Ye +5
While face recognition (FR) models have brought remarkable convenience in face verification and identification, they also pose substantial privacy risks to the public. Existing fac…
TEAM: Temporal Adversarial Examples Attack Model against Network Intrusion Detection System Applied to RNN
Ziyi Liu, Dengpan Ye, Long Tang +2
With the development of artificial intelligence, neural networks play a key role in network intrusion detection systems (NIDS). Despite the tremendous advantages, neural networks a…
Trinity Detector:text-assisted and attention mechanisms based spectral fusion for diffusion generation image detection
Jiawei Song, Dengpan Ye, Yunming Zhang
Artificial Intelligence Generated Content (AIGC) techniques, represented by text-to-image generation, have led to a malicious use of deep forgeries, raising concerns about the trus…
DIP-Watermark: A Double Identity Protection Method Based on Robust Adversarial Watermark
Yunming Zhang, Dengpan Ye, Caiyun Xie +4
The wide deployment of Face Recognition (FR) systems poses privacy risks. One countermeasure is adversarial attack, deceiving unauthorized malicious FR, but it also disrupts regula…
AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies
Rui Wang, Dengpan Ye, Long Tang +2
With the continuous improvements of deepfake methods, forgery messages have transitioned from single-modality to multi-modal fusion, posing new challenges for existing forgery dete…
Dual Defense: Adversarial, Traceable, and Invisible Robust Watermarking against Face Swapping
Yunming Zhang, Dengpan Ye, Caiyun Xie +4
The malicious applications of deep forgery, represented by face swapping, have introduced security threats such as misinformation dissemination and identity fraud. While some resea…
Feature Extraction Matters More: Universal Deepfake Disruption through Attacking Ensemble Feature Extractors
Long Tang, Dengpan Ye, Zhenhao Lu +4
Adversarial example is a rising way of protecting facial privacy security from deepfake modification. To prevent massive facial images from being illegally modified by various deep…