When data exchange advances through the electronic system, the need for information security has become a must. Protection of images and videos is important in today's visual communication system. Confidential image / video data must be shielded from unauthorized uses. Detecting and identifying unauthorized users is a challenging task. Various researchers have suggested different techniques for securing the transfer of images. In this research, the comparative study of these current technologies also addressed the types of images / videos and the different techniques of image / video processing with the steps used to process the image or video. This research classifies the two types of Encryption Algorithm, Symmetric and Encryption Algorithm, and provides a comparative analysis of its types, such as AES, MAES, RSA, DES, 3DES and BLOWFISH.

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As a result of the expansions that have taken place in the field of networking and the increase in the number of users of networks, there have recently been breakthroughs made in the techniques and methods used for network security. In this paper, a virtual private network (VPN) is proposed as a means of providing the necessary level of security for particular connections that span across vast networks. After the network performance metrics such as time delay and throughput have been accomplished, the suggested VPN is recommended for the purpose of assuring network security. In addition, artificial intelligence attack predictors and virtual private networks have been implemented with the purpose of preventing harmful activity within such connections. Using a wide variety of machine learning methods like Random Forests and Nave Bays, malicious assaults of any kind can be identified and thwarted in their tracks. Another technique for anticipating attacks is the use of an artificial neural network, which is a type of system that engages in deep learning and learns the behaviors of attacks while it is being trained so that it can then predict attacks. The results of this study demonstrate that the use of machine learning and artificial intelligence techniques can significantly improve the security and performance of virtual private networks and can effectively identify and prevent malicious attacks on networks.

Face detection is the most critical and first step in the attendance management system. The human face is non-rigid and has many differences in visual situations, scale, clarity, poses, and rotation. The precise and reliable identification was a challenge for the researcher. A variety of methods and techniques are suggested, but due to many variations, no one technique is very effective for all sorts of faces and pictures. Many techniques show good results under certain conditions, and others are successful for various types of images. Image-discriminating methods are commonly used for pattern and image analysis. Specific forms of prejudice are discussed.