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Internet of Things, Biometrics, Privacy and Security


With the emergence of the internet of things (IoT), smart sensing devices such as smartwatches and smartphones are rich with various sensors helping us with different services, including unlocking cars and validating financial transactions. But, often these services are delivered based on a user’s sensitive personal information, including demographic identity, and various sensitive data, such as heart rate. Therefore, it is important to understand how missing biometric samples can be fatal to predict a user’s identity and raise threats to the user’s IoT-connected cyber-physical space. This project will utilize machine learning and data fusion techniques on smartwatch/smartphone data to predict a user’s identity that may lead to different risks. Thereby, our findings will guide developers to develop robust authentications to foster global security.