Adaptive algorithms applied to accelerometer biometrics in a data stream context

The use of smartphone devices has increased over the last years, as illustrated by the growth in smartphone sales. These devices are currently used for several services, such as bank account access, social networks and storage of personal information. In view of this scenario, an important question arises: does authentication mechanisms already present in these devices provide enough security? Recently, a new authentication method, named accelerometer biometrics, has been proposed. This method allows the authentication of users using accelerometer data, which can be obtained from accelerometers usually present in modern smartphones. This is a clear advantage of this biometric modality, as there would be no additional cost with hardware. However, as a behavioral biometric technology, user models induced from accelerometer data may become outdated over time. This paper investigates the use of adaptation mechanisms to update user models in accelerometer biometrics in a data stream context. Practical issues regarding the usage of accelerometer data are also discussed.