Aythami Morales

TypeNet: Scaling up Keystroke Biometrics

2020

We study the suitability of keystroke dynamics to authenticate 100 K users typing free-text. For this, we first analyze to what extent our method based on a Siamese Recurrent Neural Network (RNN) is able to …

BeCAPTCHA-Type: Biometric Keystroke Data Generation for Improved Bot Detection

2022 · arXiv (Cornell University)

This work proposes a data driven learning model for the synthesis of keystroke biometric data. The proposed method is compared with two statistical approaches based on Universal and User-dependent models. These approaches are validated on …

Mobile Keystroke Biometrics Using Transformers

2022 · arXiv (Cornell University)

Among user authentication methods, behavioural biometrics has proven to be effective against identity theft as well as user-friendly and unobtrusive. One of the most popular traits in the literature is keystroke dynamics due to the …

SaFL: Sybil-aware Federated Learning with Application to Face Recognition

2023 · arXiv (Cornell University)

Federated Learning (FL) is a machine learning paradigm to conduct collaborative learning among clients on a joint model. The primary goal is to share clients' local training parameters with an integrating server while preserving their …