Extended Reality (XR) technologies, including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), offer users deeply immersive and interactive experiences, revolutionizing fields from entertainment and gaming to education and professional applications. As these technologies become integral to daily life, they increasingly collect vast amounts of sensitive personal data, such as biometrics, location, and confidential information. Thus, ensuring secure and continuous user identification becomes essential. Traditional security measures, such as passwords or two-factor authentication, are often insufficient or impractical for continuous security monitoring. Additionally, many advanced identification approaches, such as user task and iris scan, require intrusive procedures, external sensors, or high deployment costs, limiting their usability in practical AR/VR scenarios. To address these issues, this project introduces a novel approach to biometric user identification that leverages natural head movement patterns, which is a type of biometric signature inherently available in most commercial AR/VR devices, to authenticate users continuously and unobtrusively during regular device use. By embedding this behavior-based identification mechanism directly into AR/VR platforms, the research offers a new path to improving security, providing secure, continuous identification without additional hardware costs or interruptions to user experience. This initiative will enha