Review of Face Recognition Techniques for Secured Cloud Data Surveillance using Machine Learning

摘要

Face recognition techniques are used in the cloud environment for securing the cloud data from intrusion activities. Face recognition techniques help detect any kind of intrusion activities and in protecting cloud data from intrusion activities. Face recognition techniques help extract and secure the information embedded into cloud data by using different machine learning-based methods. In a cloud environment, recognition techniques can be used in identifying accurate information from the image as well as speech signals. Machine learning and deep learning-based techniques help increase the accuracy of recognition in the cloud environment. The main aim of this research is to identify efficient face recognition techniques that can be implemented in the cloud environment for securing data stored on the cloud network. Cloud data, behaviour detection, and recognition are the major components that help develop an efficient system to be implemented in a cloud environment for achieving secure data surveillance and to secure data stored on the cloud environment from any network intrusion activities. Analysis and evaluation of these components help in developing an efficient system based on machine learning techniques that help in recognizing different activities and in detecting intruder activities in the cloud environment. Classification of all the system components helps in identifying efficient machine learning-based face recognition system for obtaining secure cloud data surveillance.