Mobile Phone Anti-theft Method Based on Mobile Track and User Characteristic

The cell phones are becoming more common and turn into a part of our life. While being convenient to use, the users are exposed to take the risk of privacy leakage due to a large amount of private information is stored on their cell phones. This paper proposes an anti-theft method based on motion trajectory and user features, which can alarm the theft in the process, and curb the theft in the initial stage. We uses the cellphone attitude detection algorithm in human coordinate system to conrm phone status, and proposed to calculate the motion trajectory based on Iterative Kalman Filter Inertial Navigation Algorithm. By the trajectory of the phone as it takes out and the features contained in the movement, a warning will be given when thefts are taking place. We evaluate the main modules of our method through a large number of experiments. Results show that the overall accuracy of the system can reach more than 90.33%.