Devices and methods for smartphone impostor detection using behavioral and environmental data are provided. Impostors are attackers who take control of an electronic device (e.g., a smartphone) and gain access to confidential and private information of a legitimate user. Embodiments described herein propose a defense-in-depth mechanism to detect impostors quickly with simple deep learning algorithms, which can achieve better detection accuracy than previous works. Embodiments then consider protecting the privacy of the behavioral and/or environmental data (e.g., collected by one or more sensors) of a user by not exposing it outside the protected device.

A recurrent neural network (RNN)-based deep learning algorithm is proposed which uses only sensor data of the legitimate user to learn their normal behavior. Prediction error distribution (PED) is used to enhance the detection accuracy. In some embodiments, a minimalist hardware module, dubbed smartphone impostor detector (SID), can be designed and integrated into smartphones for self-contained impostor detection. SID can support real-time impostor detection at a very low hardware cost and energy consumption compared to other RNN accelerators.

An exemplary embodiment provides a mobile device. The mobile device includes one or more sensors and an impostor detection module coupled to the one or more sensors. The impostor detection module is configured to receive at least one of behavioral data or environmental data from the one or more sensors and detect if an impostor is using the mobile device based on anomalies in the at least one of the behavioral data or the environmental data.

Another exemplary embodiment provides a method for detecting an impostor. The method includes receiving sensor data from an electronic device, analyzing the sensor data to determine a behavioral characteristic corresponding to a user of the electronic device, and determining if the user is an impostor by comparing the behavioral characteristic with expected behavior of an authorized user.

Those skilled in the art will appreciate the scope of the present disclosure and realize additional aspects thereof after reading the following detailed description of the preferred embodiments in association with the accompanying drawing figures.