6 citations · 25 across the 35 of their papers we have counts for
35 papers
Personalizing LLM Agent Memory Using Biometrics
Yanhong Qian, Qingguo Meng, Shihao Ding +4
Personalized memory helps LLM agents deliver stable, tailored assistance by storing and reusing user-specific data across interactions. In multi-user scenarios, however, retrieval…
AngelFingerprint: A Traceable, Explainable, and White-Box Stealthy Watermark for Text-Guided Image Editing
Bo-Han Kung, Futa Waseda, Ching-Chun Chang +2
Text-guided diffusion editing raises disinformation concerns, making reliable image provenance essential. While watermarks are commonly used for this purpose, most methods carry a…
Retrosynthesis of Synthetic Media for Explainable AI Provenance Forensics
Yijie Lin, Ching-Chun Chang, Isao Echizen +2
With the rapid proliferation of generative models on Machine Learning as a Service (MLaaS) platforms, reliably tracing the provenance of synthetic media without modifying generator…
Semantic Color Naturalness Breaker: Preventing Illegitimate Colorization via Content-Aware Color Priors
Yuki Nii, Futa Waseda, Ching-Chun Chang +1
Automatic image colorization enables large-scale and low-cost reuse of grayscale media (e.g., manga panels and archival photographs), facilitating unauthorized reuse and redistribu…
Beyond Standard Benchmarks: A Systematic Audit of Vision-Language Model's Robustness to Natural Semantic Variation Across Diverse Tasks
Jia Chengyu, AprilPyone MaungMaung, Huy H. Nguyen +2
Recent advances in vision-language models (VLMs) trained on web-scale image-text pairs have enabled impressive zero-shot transfer across a diverse range of visual tasks. However, c…
GFT-GCN: Privacy-Preserving 3D Face Mesh Recognition with Spectral Diffusion
Hichem Felouat, Hanrui Wang, Isao Echizen
3D face recognition offers a robust biometric solution by capturing facial geometry, providing resilience to variations in illumination, pose changes, and presentation attacks. Its…
Uncolorable Examples: Preventing Unauthorized AI Colorization via Perception-Aware Chroma-Restrictive Perturbation
Yuki Nii, Futa Waseda, Ching-Chun Chang +1
AI-based colorization has shown remarkable capability in generating realistic color images from grayscale inputs. However, it poses risks of copyright infringement -- for example,…
A Controllable 3D Deepfake Generation Framework with Gaussian Splatting
Wending Liu, Siyun Liang, Huy H. Nguyen +1
We propose a novel 3D deepfake generation framework based on 3D Gaussian Splatting that enables realistic, identity-preserving face swapping and reenactment in a fully controllable…
Tell-Tale Watermarks for Explanatory Reasoning in Synthetic Media Forensics
Ching-Chun Chang, Isao Echizen
The rise of synthetic media has blurred the boundary between reality and fabrication under the evolving power of artificial intelligence, fueling an infodemic that erodes public tr…
Measuring Human Involvement in AI-Generated Text: A Case Study on Academic Writing
Yuchen Guo, Zhicheng Dou, Huy H. Nguyen +3
Content creation has dramatically progressed with the rapid advancement of large language models like ChatGPT and Claude. While this progress has greatly enhanced various aspects o…
AnimeDL-2M: Million-Scale AI-Generated Anime Image Detection and Localization in Diffusion Era
Chenyang Zhu, Xing Zhang, Yuyang Sun +2
Recent advances in image generation, particularly diffusion models, have significantly lowered the barrier for creating sophisticated forgeries, making image manipulation detection…
DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion
Hanrui Wang, Shuo Wang, Chun-Shien Lu +1
Face recognition poses serious privacy risks due to its reliance on sensitive and immutable biometric data. While modern systems mitigate privacy risks by mapping facial images to…
Chronology of Multi-Agent Interactions for Provenance of Evolving Information
Ching-Chun Chang, Isao Echizen
Provenance is the chronological history of things, resonating with the fundamental pursuit to uncover origins, trace connections, and situate entities within the flow of space and…
Exploring Active Data Selection Strategies for Continuous Training in Deepfake Detection
Yoshihiko Furuhashi, Junichi Yamagishi, Xin Wang +2
In deepfake detection, it is essential to maintain high performance by adjusting the parameters of the detector as new deepfake methods emerge. In this paper, we propose a method t…
Steganography Beyond Space-Time with Chain of Multimodal AI
Ching-Chun Chang, Isao Echizen
Steganography is the art and science of covert writing, with a broad range of applications interwoven within the realm of cybersecurity. As artificial intelligence continues to evo…
Cyber-Physical Steganography in Robotic Motion Control
Ching-Chun Chang, Yijie Lin, Isao Echizen
Steganography, the art of information hiding, has continually evolved across visual, auditory and linguistic domains, adapting to the ceaseless interplay between steganographic con…
GreedyPixel: Fine-Grained Black-Box Adversarial Attack Via Greedy Algorithm
Hanrui Wang, Ching-Chun Chang, Chun-Shien Lu +2
Deep neural networks are highly vulnerable to adversarial examples, which are inputs with small, carefully crafted perturbations that cause misclassification -- making adversarial…
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…