User Authentication Method for Smart Glasses using Gaze Information of Registered Known Images and AI-generated Unknown Images

It is important to use user authentication methods, such as bio-metric and behavior-based user authentications, for smart glasses. Smart glasses can collect data containing privacy information such as videos, audio, and behavioral information, as well as access personal information like emails and social networking services (SNS). This paper proposes a method that uses gaze information for user authentication by displaying an image known only to the user who registered it in advance, and several images generated from the registered image. These images are displayed on the screen of the smart glasses. Gaze information is obtained and authentication is conducted using an LSTM. Evaluation experiments were carried out by obtaining gaze information from eight subjects. Data from five subjects were obtained using a stationary device, while data from the remaining three subjects were obtained using a glasses-type device. The overall results showed 81.2% and 84.4% authentication success rates using the stationary device and the glasses-type device, respectively.