Advanced Authentication Method by Geometric Data Analysis Based on User Behavior and Biometrics for IoT Device with Touchscreen

Abstract

The Internet of Things (IoT) technology is rapidly being applied to real life, but the application of a corresponding secure and convenient authentication method is still in significant challenge. So far, pattern, password and fingerprint authentication are the most used methods, but it is important to address various security vulnerabilities and limitations of these approaches. In the case of fingerprint recognition, additional hardware such as a fingerprint scanner is required, which causes cost issues and could be vulnerable to fingerprint theft. To solve this problem, this paper proposes a model that uses both biometric and behavioral authentication at the same time. This method exploits the biometric authentication that measures the length of the contact region that occurs when three fingers are placed side by side on the touch screen or pad. In addition, it utilizes the behavioral authentication itself using three-finger L-shape touch, as well as secure geometric information generated by smart watch such as acceleration sensors. Therefore, this proposed model will be useful to implement more secure, rapid and user-friendly way of authentication in many practical busy and buzzling field where deal with sensitive private information.