Facial Biometrics-Driven Feature Encoding and Deep Learning Integration for Secure Password Retrieval

The proposed system includes face recognition-based systems designed for secure identity verification and decentralized data storage. The working is supposed to be done in three phases: data capture, training of the machine learning model, and decentralized data storage. Collection in the first phase will include face images of individuals and government-issued identification details, such as Aadhar and PAN. A machine learning model will be trained in the second phase for improving the accuracy in the face recognition process. The third phase ensures secure storage of the recognized faces and associated personal data through a decentralized approach similar to blockchain technology. Security, privacy, and resilience against tampering are further developed in this design. The proposed system will reliably meet the application requirements that involve strong authentication processes and protection of data, therefore making the sectors using these systems include government services and secured personal data management.