Utilizing passive wearable devices to capture device interaction data for supplementary authentication

Abstract

The technology described herein is directed towards using a wearable passive metasurface (e.g., in the form of 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 correspond to user interaction pattern data (user activity profile data) during times of user interaction with the computer. In one implementation, a multi-modal machine learning (ML) classifier processes features of the user interaction pattern data, extracted from time and frequency domain analyses, to recognize habitual interaction patterns of a user, as well as detect any deviations from the user's ordinary interaction behavior, possibly indicating a different user. An interaction pattern that is associated with the user can facilitate ongoing authentication. Deviations from a user's typical interaction pattern also are detectable, whereby the system can generate additional authentication requests or take other security-related actions.