Secured and High Performance Distributed Big Data Storage in Cloud Systems

Big Data Security and privacy are key concerns for cloud computing. At the initial stage, security was not considered for processing Big Data because of insufficient research and adequate security technology. Now researchers have to think new ways for cloud storage and Big Data security to overcome exiting security challenges of Big Data storage. For rapid Big Data processing, encryption is often considered as a big obstacle as clear data processing is much faster than encrypted data. But for cloud system, encrypted data processing is not a big deal because of massive processing power of cloud systems. So encryption will not be an obstacle and degrade the performance to process encrypted Big Data at cloud. There is a big challenge now to store and provide security in small chunk in cloud system and also key management. This paper provides novel approach for Big Data security over cloud namely Secured and High Performance Distributed Big Data Storage (SH-DBDS) model. Data will be split and uploaded for distributed cloud storage system. Single split data will be worthless until and unless joined with the other parts of the data. In this paper, an algorithm has been provided to split and join the data. Experimentation is performed with different data sets (10MB-1GB) at local system and AWS cloud and performance is measured. Evaluation is done considering the security and performance of Big Data.