Author : Srinivas Murri

Every day, enormous amounts of data are produced at an exponential pace. Therefore, in order to get valuable insights into the modern world, analytics over data is unavoidable. Big Data (BD) makes good judgments and is strong in important applications. Big Data’s meteoric rise in cloud computing has brought both new possibilities and new difficulties to the management and processing of enormous datasets. Hadoop and MapReduce are two state-of-the-art technologies used in today’s world to face the heterogeneous high velocity, high variety and huge volume of data. CSPs such as AWS provide highly effective, low-cost solutions for managing and analyzing Big Data, yet security and privacy issues are still critical because of the highly sensitive nature of the information and due to the challenges brought about by intercloud migrations and high flash data rates. The present review paper aims to identify the key data security concerns in Big Data cloud computing models to analyze data privacy and integrity, availability, access control and multi-tenancy risks. It also provides an overview of kinds of security threats: encryption methods, methods of data-sharing safely, access-control mechanisms, and machine-learning-based anomaly detection that can protect from these threats. Furthermore, it emphasizes using scalable and multi-layer security architecture for the secure management of critical data through Big Data applications and maintaining their performance and capacity. Through these issues with sound security measures being addressed, corporations can explore the Big Data cloud environment for safe and reliable data processing and veracity of such environment.

Keywords: Big Data, cloud computing environments, data security, cloud service providers, Amazon Web Services, Challenges, Solutions.