TouchMetric, a mobile application developed for Android and iOS, used for the purpose of testing a machine learning model for the development of a CPoP feature.
The rapid and ubiquitous adoption of mobile device use has propagated our dependence on their ability to keep individuals within our society connected. Mobile devices are now a primary method of communication and connecting to the internet for many. As with any technology, with wide-adoption comes many challenges. Due to the nature of mobile communication, data transmission is the fundamental method of connecting users on the network. As with any form of data transmission, data security is a key concern which must be taken into account. Several methods of user authentication and authorization exist for the purpose of privacy preservation and security and are widely used in mobile systems. One such method is the Continuous Proof of Presence (CPoP) authentication. CPoP has the potential to provide an extra layer of security to users in data sensitive industries, such as the security sector, government and corporate administration, and healthcare. In this work we present TouchMetric, a mobile application developed for Android and iOS, used for the purpose of testing a machine learning model for the development of a CPoP feature.
The published paper is available at: https://link.springer.com/article/10.1007/s41870-019-00306-w
The Android application is also available on Google Play: https://play.google.com/store/apps/details?id=com.touchmetric