Keystroke dynamics is a behavioural biometric utilised for user identification and authentication. We propose a new set of features based on the distance between keys on the keyboard, a concept that has not been considered before in keystroke dynamics. We combine flight times, a popular metric, with the distance between keys on the keyboard and call them as Distance Enhanced Flight Time features (DEFT). This novel approach provides comprehensive insights into a person's typing behaviour, surpassing typing velocity alone. We build a DEFT model by combining DEFT features with other previously used keystroke dynamic features. The DEFT model is designed to be device-agnostic, allowing us to evaluate its effectiveness across three commonly used devices: desktop, mobile, and tablet. The DEFT model outperforms the existing state-of-the-art methods when we evaluate its effectiveness across two datasets. We obtain accuracy rates exceeding 99% and equal error rates below 10% on all three devices.

翻译：击键动态是一种用于用户识别与认证的行为生物特征。我们提出了一种基于键盘按键间距离的新型特征集，这一概念在击键动态研究中此前尚未被考虑。我们将飞行时间这一常用度量与按键间距离相结合，并将其称为距离增强飞行时间特征（DEFT）。这种新颖方法能够全面洞察个体的打字行为，超越了仅依赖打字速度的局限性。我们通过将DEFT特征与其他先前使用的击键动态特征相结合，构建了DEFT模型。该模型设计为设备无关的，使我们能够评估其在三种常用设备（台式机、移动设备和平板电脑）上的有效性。在两个数据集上评估其效果时，DEFT模型的表现优于现有最先进方法。在所有三种设备上，我们均获得了超过99%的准确率和低于10%的等错误率。