70 citations · 163 across the 12 of their papers we have counts for
12 papers
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
Chao Shuai, Jieming Zhong, Shuang Wu +6
Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection methods are typically inadequate in generalizability, with a tendency to overfit to ima…
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues
Kun Pan, Yin Yifang, Yao Wei +6
The malicious use and widespread dissemination of deepfake pose a significant crisis of trust. Current deepfake detection models can generally recognize forgery images by training…
SurrogatePrompt: Bypassing the Safety Filter of Text-to-Image Models via Substitution
Zhongjie Ba, Jieming Zhong, Jiachen Lei +5
Advanced text-to-image models such as DALLE 2 and Midjourney possess the capacity to generate highly realistic images, raising significant concerns regarding the potential p…
Action Recognition with Multi-stream Motion Modeling and Mutual Information Maximization
Yuheng Yang, Haipeng Chen, Zhenguang Liu +5
Action recognition has long been a fundamental and intriguing problem in artificial intelligence. The task is challenging due to the high dimensionality nature of an action, as wel…
Privacy-preserving Adversarial Facial Features
Zhibo Wang, He Wang, Shuaifan Jin +7
Face recognition service providers protect face privacy by extracting compact and discriminative facial features (representations) from images, and storing the facial features for…
Feature Importance-aware Transferable Adversarial Attacks
Zhibo Wang, Hengchang Guo, Zhifei Zhang +3
Transferability of adversarial examples is of central importance for attacking an unknown model, which facilitates adversarial attacks in more practical scenarios, e.g., black-box…
Optimizing Privacy-Preserving Outsourced Convolutional Neural Network Predictions
Minghui Li, Sherman S. M. Chow, Shengshan Hu +3
Convolutional neural network is a machine-learning model widely applied in various prediction tasks, such as computer vision and medical image analysis. Their great predictive powe…
Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution
Shengshan Hu, Chengjun Cai, Qian Wang +4
Searchable symmetric encryption (SSE) allows the data owner to outsource an encrypted database to a remote server in a private manner while maintaining the ability for selectively…
advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns
Zhibo Wang, Siyan Zheng, Mengkai Song +3
Person re-identification (re-ID) is the task of matching person images across camera views, which plays an important role in surveillance and security applications. Inspired by gre…
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning
Zhibo Wang, Mengkai Song, Zhifei Zhang +3
Federated learning, i.e., a mobile edge computing framework for deep learning, is a recent advance in privacy-preserving machine learning, where the model is trained in a decentral…
PatternListener: Cracking Android Pattern Lock Using Acoustic Signals
Man Zhou, Qian Wang, Jingxiao Yang +4
Pattern lock has been widely used for authentication to protect user privacy on mobile devices (e.g., smartphones and tablets). Given its pervasive usage, the compromise of pattern…
Active Link Obfuscation to Thwart Link-flooding Attacks for Internet of Things
Xuyang Ding, Feng Xiao, Man Zhou +1
The DDoS attack is a serious threat to Internet of Things (IoT). As a new class of DDoS attack, Link-flooding attack (LFA) disrupts connectivity between legitimate IoT devices and…