Security and Privacy Considerations in Cloud-Based Big Data Analytics

Abstract

The paper aims at critically analysing the issues of security and privacy in cloud-based big data analytics as one of the innovative fields which employs the opportunities of cloud computing and big data analysis. The paper focuses on the specific issues concerned with implementation of these technologies, namely data security, data integrity, identity, and data protection legislation. It offers a comprehensive understanding of numerous security solutions and privacy-captivating strategies which include, cryptology, protected secure multi-party computation, and differential privacy. They also describe such new technologies as quantum computation and machine learning and connect them with threats and risks. Based on the analysis of the state of the art in literature and research applied in the cloud big data context, this study seeks to present benchmarks for cloud big data analytics security and present both recommendations to practitioners and directions for future research in the field.