Fake Fingerprint

Fake fingerprints, or fingerprint spoofs, pose a significant threat to biometric security systems, prompting research focused on both their creation and detection. Current research employs generative adversarial networks (GANs), diffusion models, and convolutional neural networks (CNNs), often combined with handcrafted features or wavelet transforms, to synthesize realistic fake fingerprints and develop robust detection methods. The primary objective is to improve the accuracy and robustness of liveness detection, differentiating genuine fingerprints from spoofs across various materials and attack scenarios, thereby enhancing the security and reliability of fingerprint-based authentication systems. This research is crucial for maintaining the integrity of biometric security in diverse applications.