RESULT ANALYSIS OF BIG DATA ANALYTICAL ARCHITECTURE FOR REMOTE SENSING APPLICATION IN REAL TIME

Abstract: In recent years, big data became a hot analysis topic. The increasing quantity of big data additionally will increase the possibility of breaching the privacy of individuals. Since big data need high procedure power and large storage, distributed systems are used. As multiple parties are involved in these systems, the risk of privacy violation is increased. There are varieties of privacy-preserving mechanisms developed for privacy protection at different stages (e.g., data generation, data storage, and data processing) of an enormous data life cycle. The goal of this work is to provide a comprehensive summary of the privacy preservation mechanisms in big data and present the challenges for existing mechanisms. Specifically, during this work illustrate the infrastructure of big data and also the state-of-the-art privacy-preserving mechanisms in every stage of the big data life cycle. Moreover, discuss the challenges and future analysis directions related to privacy preservation in big data.

Keywords: Big Data, DADU, DPU, land and sea area, Real-time, remote senses, RSDU.