6 citations · 25 across the 35 of their papers we have counts for
13 papers · 1 filter
Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systems
Muyao Niu, Zhuoxiao Li, Yifan Zhan +3
Many surveillance cameras switch between daytime and nighttime modes based on illuminance levels. During the day, the camera records ordinary RGB images through an enabled IR-cut f…
Steganography in Game Actions
Ching-Chun Chang, Isao Echizen
The exchange of messages has always carried with it the timeless challenge of secrecy. From whispers in shadows to the enigmatic notes written in the margins of history, humanity h…
Hypnopaedia-Aware Machine Unlearning via Psychometrics of Artificial Mental Imagery
Ching-Chun Chang, Kai Gao, Shuying Xu +3
Neural backdoors represent insidious cybersecurity loopholes that render learning machinery vulnerable to unauthorised manipulations, potentially enabling the weaponisation of arti…
Agentic Copyright Watermarking against Adversarial Evidence Forgery with Purification-Agnostic Curriculum Proxy Learning
Erjin Bao, Ching-Chun Chang, Hanrui Wang +1
With the proliferation of AI agents in various domains, protecting the ownership of AI models has become crucial due to the significant investment in their development. Unauthorize…
LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification
Shuhan Cui, Huy H. Nguyen, Trung-Nghia Le +2
Amid the proliferation of forged images, notably the tsunami of deepfake content, extensive research has been conducted on using artificial intelligence (AI) to identify forged con…
Minimal Cascade Gradient Smoothing for Fast Transferable Preemptive Adversarial Defense
Hanrui Wang, Ching-Chun Chang, Chun-Shien Lu +3
Adversarial attacks persist as a major challenge in deep learning. While training- and test-time defenses are well-studied, they often reduce clean accuracy, incur high cost, or fa…
Mitigating Backdoor Attacks using Activation-Guided Model Editing
Felix Hsieh, Huy H. Nguyen, AprilPyone MaungMaung +2
Backdoor attacks compromise the integrity and reliability of machine learning models by embedding a hidden trigger during the training process, which can later be activated to caus…
Exploring Self-Supervised Vision Transformers for Deepfake Detection: A Comparative Analysis
Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
This paper investigates the effectiveness of self-supervised pre-trained vision transformers (ViTs) compared to supervised pre-trained ViTs and conventional neural networks (ConvNe…
Image-Text Out-Of-Context Detection Using Synthetic Multimodal Misinformation
Fatma Shalabi, Huy H. Nguyen, Hichem Felouat +2
Misinformation has become a major challenge in the era of increasing digital information, requiring the development of effective detection methods. We have investigated a novel app…
Leveraging Chat-Based Large Vision Language Models for Multimodal Out-Of-Context Detection
Fatma Shalabi, Hichem Felouat, Huy H. Nguyen +1
Out-of-context (OOC) detection is a challenging task involving identifying images and texts that are irrelevant to the context in which they are presented. Large vision-language mo…
Enhancing Robustness of LLM-Synthetic Text Detectors for Academic Writing: A Comprehensive Analysis
Zhicheng Dou, Yuchen Guo, Ching-Chun Chang +2
The emergence of large language models (LLMs), such as Generative Pre-trained Transformer 4 (GPT-4) used by ChatGPT, has profoundly impacted the academic and broader community. Whi…
Cross-Attention Watermarking of Large Language Models
Folco Bertini Baldassini, Huy H. Nguyen, Ching-Chung Chang +1
A new approach to linguistic watermarking of language models is presented in which information is imperceptibly inserted into the output text while preserving its readability and o…
Surface Normal Estimation with Transformers
Barry Shichen Hu, Siyun Liang, Johannes Paetzold +3
We propose the use of a Transformer to accurately predict normals from point clouds with noise and density variations. Previous learning-based methods utilize PointNet variants to…