6 papers
XSA-MAD: Cross-modal Semantic Alignment for Morphing Attack Detection
Jie Jin, Mahiro Tokumasu, Yu Makino +2
Morphing attacks pose a serious threat to face recognition systems. However, existing image-based morphing attack detection (MAD) methods often generalize poorly to unseen generati…
Face Re-morphing: Differential Morphing Attack Detection via Feature-Space Similarity Changes
Jie Jin, Masakatsu Nishigaki, Tetsushi Ohki
Face morphing attacks pose a serious threat to face recognition systems because a single morphed document image can be matched to multiple contributors. Differential morphing attac…
Can We End the Cat-and-Mouse Game? Simulating Self-Evolving Phishing Attacks with LLMs and Genetic Algorithms
Seiji Sato, Tetsushi Ohki, Masakatsu Nishigaki
Anticipating emerging attack methodologies is crucial for proactive cybersecurity. Recent advances in Large Language Models (LLMs) have enabled the automated generation of phishing…
Multibiometrics Using a Single Face Image
Koichi Ito, Taito Tonosaki, Takafumi Aoki +2
Multibiometrics, which uses multiple biometric traits to improve recognition performance instead of using only one biometric trait to authenticate individuals, has been investigate…
Leveraging Intermediate Features of Vision Transformer for Face Anti-Spoofing
Mika Feng, Koichi Ito, Takafumi Aoki +2
Face recognition systems are designed to be robust against changes in head pose, illumination, and blurring during image capture. If a malicious person presents a face photo of the…
Enhancing Remote Adversarial Patch Attacks on Face Detectors with Tiling and Scaling
Masora Okano, Koichi Ito, Masakatsu Nishigaki +1
This paper discusses the attack feasibility of Remote Adversarial Patch (RAP) targeting face detectors. The RAP that targets face detectors is similar to the RAP that targets gener…