6 papers
Breaking High Confidence: Practical Face Impersonation under High-Security Thresholds
Changjin Kim, Seunghun Paik, Dongsoo Kim +1
Face recognition systems (FRSs) are increasingly deployed in critical real-world services for authentication, such as banking applications and airport identity checks, necessitatin…
Casting the Net! Revisiting MasterFace Impersonation Attacks
Seunghun Paik, Sunpill Kim, Chanwoo Hwang +1
Impersonation is a fundamental security threat in face recognition systems (FRSs). While the security of FRSs has been challenged by various attack vectors, under realistic adversa…
Naïve Exposure of Generative AI Capabilities Undermines Deepfake Detection
Sunpill Kim, Chanwoo Hwang, Minsu Kim +1
Generative AI systems increasingly expose powerful reasoning and image refinement capabilities through user-facing chatbot interfaces. In this work, we show that the naïve exposur…
Scores Know Bobs Voice: Speaker Impersonation Attack
Chanwoo Hwang, Sunpill Kim, Yong Kiam Tan +6
Advances in deep learning have enabled the widespread deployment of speaker recognition systems (SRSs), yet they remain vulnerable to score-based impersonation attacks. Existing at…
Non-Adaptive Adversarial Face Generation
Sunpill Kim, Seunghun Paik, Chanwoo Hwang +2
Adversarial attacks on face recognition systems (FRSs) pose serious security and privacy threats, especially when these systems are used for identity verification. In this paper, w…
IDFace: Face Template Protection for Efficient and Secure Identification
Sunpill Kim, Seunghun Paik, Chanwoo Hwang +3
As face recognition systems (FRS) become more widely used, user privacy becomes more important. A key privacy issue in FRS is protecting the user's face template, as the characteri…