Enhanced Laptop Security with Biometric-Based Multifactor Authentication

Providing authentication and security to laptop is one of the challenges that we are facing today. The conventional techniques are vulnerable to spoof attacks using masks, images, and videos, facial recognition provides a practical but safe authentication solution. The present work uses modern liveness detection methods into the upgraded laptop authentication to improve security and stop undesired consumption. With random challenges to validate user presence, micro expression identification, and real-time user interaction stimuli, the proposed approach combines active and passive liveness detection. OTP fallback authentication is included as a backup should liveness detection be inadequate. The suggested method integrates interactive authentication processes to prevent complex spoofing attacks, in contrast to the current face recognition-based authentication solutions that rely on static verification procedures. The system guarantees strong protection without sacrificing user experience because it was designed with security and usability in mind. The accuracy, erroneous acceptance and rejection rates, and spoofing resistance are measured using a robust assessment framework. The usefulness of using these techniques on business laptops is confirmed by experimental findings, which provide a balance between security, usability, and efficiency. This study contributes to the current body of work on secure, user-oriented authentication protocols, offering a feasible solution for the strengthening of laptop security and paving the way for further research into biometric authentication of mobile computers.