Behavioural biometrics is becoming more and more popular. It is hard to find a sensor that is embedded in a mobile/wearable device, which cannot be exploited to extract behavioural biometric data. In this study, the authors give the reader an overview of mobile device behavioural biometric data and how this data is used in experiments, especially examining papers that introduce new datasets. They will not examine performance accomplished by the algorithms used since a system's performance is enormously affected by the data used, its amount and quality. Altogether, 40 papers are examined, assessing how often they are cited, have databases published, what modality data are collected, and how the data is used. They offer a roadmap that should be taken into account when designing behavioural data collection and using collected data. They further look at the General Data Protection Regulation, and its significance to the scientific research in the field of biometrics. It is possible to conclude that there is a need for publicly available datasets with comprehensive experimental protocols, similarly established in facial recognition.

中文翻译：

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移动行为生物识别技术背后的数据–调查

行为生物识别技术变得越来越流行。很难找到嵌入在移动/可穿戴设备中的传感器，该传感器无法被用来提取行为生物特征数据。在这项研究中，作者为读者提供了移动设备行为生物特征数据的概述，以及如何在实验中使用这些数据，尤其是检查引入了新数据集的论文。由于系统的性能会受到所使用的数据，数据量和质量的极大影响，因此他们将不会检查所使用算法所实现的性能。总共检查了40篇论文，评估了它们被引用的频率，发布了数据库，收集了哪些形态数据以及如何使用这些数据。它们提供了设计行为数据收集和使用收集的数据时应考虑的路线图。他们进一步研究了《通用数据保护条例》及其对生物识别领域科学研究的意义。可以得出结论，需要具有类似面部识别中建立的全面实验方案的公开可用数据集。