FENG X.

Face presentation attack detection (PAD) has become a clear and present threat for face recognition systems and many countermeasures have been proposed to mitigate it. In these countermeasures, some of them use the features directly extracted from well-known color spaces (e.g., RGB, HSV and YCbCr) to distinguish the fake face images from the...

Face presentation attacks have become a major threat against face recognition systems and many countermeasures have been proposed over the past decade. However, most of them are devoted to 2D face presentation attack detection, rather than 3D face masks. Unlike the real face, the 3D face mask is usually made of resin materials and has a smooth...

Adversarial reprogramming allows stealing computational resources by repurposing machine learning models to perform a different task chosen by the attacker. For example, a model trained to recognize images of animals can be reprogrammed to recognize medical images by embedding an adversarial program in the images provided as inputs. This attack...

Adversarial reprogramming allows repurposing a machine-learning model to perform a different task. For example, a model trained to recognize animals can be reprogrammed to recognize digits by embedding an adversarial program in the digit images provided as input. Recent work has shown that adversarial reprogramming may not only be used to abuse...

In recent years, image fusion methods based on deep networks have been proposed to combine infrared and visible images for achieving better fusion image. However, issues such as limited training data, scarce reference images and misalignment of multi-source images, still limit the fusion performance. To address these problems, we propose an...

We investigated the threat level of realistic attacks using latent fingerprints against sensors equipped with state-of-art liveness detectors and fingerprint verification systems which integrate such liveness algorithms. To the best of our knowledge, only a previous investigation was done with spoofs from latent prints. In this paper, we focus...

Deepfake refers to using artificial intelligence (AI) and machine learning techniques to create compelling and realistic media content, such as videos, images, or recordings, that appear real but are fake. The most common form of deepfake involves using deep neural networks to replace or superimpose faces in existing videos or images on top of...

The advantages of deepfakes in many applications are counterbalanced by their malicious use, for example, in reply-attacks against a biometric system, identification evasion, and people harassment, when they are widespread in social networks and chatting platforms (cyberbullying) as recently documented in newspapers. Due to its "arms-race"...