Long-term pattern recognition using proximity detection for security applications

Abstract

The technology described herein is directed towards using a wearable passive metasurface (e.g., configured as a ring) to reflect signals representative of user interaction with computer peripheral devices (e.g., a mouse and keyboard) coupled to a computing device. The reflected signals indicate current user interaction with the device obtained over a timeframe. A short term classifier model set processes features of the user interaction patterns, extracted from time and frequency domain analyses, to recognize activity from the interaction pattern data of a user, as well as detect any deviations from the user's ordinary interaction behavior, possibly indicating a different user. A long term classification model inputs the user interaction pattern data and the recognized activity, to output authentication response data, such as confidence level data, for comparison with a confidence level threshold, to determine via the interaction pattern data whether the user is an authorized user of the computing device.