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

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