A Hybrid Framework for Privacy Protecting Mobile Systems

Abstract

Now a days the obtainability of smart Phones, cameras and sensors are highly increased and becomes the important part of our daily life. Due to the usage of these devices huge data is produced and is placed on local platform. Local platforms are not able to perform exhaustive calculations. Cloud services are used for storing huge data that is produced from mobiles, sensors and cameras.Advances in machine learning and computer vision provide huge cloud services with ability of content analysis and many other facilities. But suffers from unwanted privacy risks to users or individuals. In this paper our major focusing point are the privacy preserving techniques we proposed a hybrid framework also feature extractor and classification approaches for machine learning. Noise addition feature is also use to enhance security. Our proposed solution reduced the privacy ricks.