Biometric Signature

Biometric signature verification aims to authenticate individuals based on their unique writing characteristics, captured digitally as online signatures. Current research heavily focuses on improving accuracy and security using advanced machine learning models, such as recurrent neural networks (RNNs), particularly LSTMs, and transformers, addressing challenges like forgery detection and variations in writing styles. These advancements are crucial for enhancing the security and usability of biometric authentication systems in various applications, including e-security and mobile authentication, while simultaneously mitigating presentation attacks.