DISCOVERY OF VIRULENT APPS AND FAKE GRADING IN PLAY STORE

Existing content-based analysis tools not only cause high complexity and cost, but they also fail to handle large levels of files effectively. The proposed RTS methodology is implemented as a system remedy that can work on existing systems, such as the Hadoop file system, using the general interface of the file system and the use of information correlation properties. This document presents an almost real-time plan known as RTS to help an efficient and profitable search data analysis within the cloud. RTS extracts key property information of the given type by multidimensional features to represent these details in multidimensional vectors. An intuitive idea would be to significantly reduce the number of images used by analyzing only the most representative one instead of everything, at least once the mobile phone has an energy limit. RTS uses VFS operations to help semantic grouping. We can get the data from the closet of the page to help send them to the devil. We made a real-world situation of use in which children informed in a very busy environment are identified in time by analyzing 60 million images with RTS. RTS is created to exploit the correlation property of information through the use of hashing and a structured and manageable addressing.