This survey report provides a comprehensive overview of the state-of-the-art techniques, methodologies in the field of identity verification and authentication using face and object detection. It is of the utmost importance in today's digital age to protect the identities of students in educational institutions. Face Recognition uses deep learning techniques to validate student identity and authenticate them. Students’ identities can be verified through traditional methods, such as ID cards, which are susceptible to fraud and security breaches. To enhance the security of the educational system, deep learning algorithms offer a robust and reliable solution. To provide real-time object detection, the proposed methodology uses the YOLO algorithm with CNN. Techniques used in this algorithm, such as bounding box regression, residual blocks, and IOUs. By utilizing deep neural networks, this methodology aims to provide an accurate and effective solution for vulnerabilities such as fraud identities and also impose penalty who impose penalty on the students who violates rules and regulations of the educational institutes