Enhancing Database Security for Facial Recognition using Fernet Encryption Approach

With the evolving technologies in Artificial Intelli-gence (AI), Cloud Service, IoT and many other domains, activities and work have become easier for humans. The video surveillance system can also be enhanced with the help of these three main domains. In the proposed system, the database containing all the known face image file data with their corresponding name has been created on cloud platforms. The data sent to the cloud database has also been secured by encrypting it using Fernet cryptography technique. This ensures that the data on the cloud services is secured as the key required for decrypting the database data is present on the client side only. The known faces that are stored on the cloud service platform saves system space and make the database remotely accessible. It recognizes each face in the video file and matches them with the cloud database image files and helps to distinguish the known and unknown faces in a video file. The proposed work can be used to extract the key region of interest from a video file by the time stamp that are collected along with the matching known faces from the video. Also, the approach can be applied in places where facial biometric scan is used, and in security and surveillance system at various places like shopping mall, markets with a little modification. The identified faces from the video are highlighted by a blue box with the corresponding name at the top of the box and a notification is also sent to the client device with timestamp.