SECURITY AND PRIVACY TECHNIQUE IN BIG DATA: A REVIEW

Abstract

The importance of Big Data as a foundational component of the AI and ML landscape is not going away anytime soon. As a result, the past fifteen years have seen a tremendous investment in Big Data research. The purpose of this literature review is to compile the most recent results from Big Data studies conducted over the past fifteen years. The study will address questions about the main applications of Big Data analytics, the main challenges and limitations encountered by researchers, and the present and future state of Big Data studies. The review follows a predetermined procedure that automatically examines five major digital libraries. Among  more recent branches of computer science is the study of large amounts of data. Social media, online shopping, blogs, financial institutions, healthcare providers, transactions, websites, applications, opinion forums, and a host of other sources all contribute to the accumulation of data. Various businesses, notably healthcare, make excellent use of it after processing. For data processing and analysis in the industrial sector, these massively generated datasets are indispensable. In order to investigate the value and potential of big data in healthcare and industrial processing applications, this article surveys the published works of numerous writers who have helped with data collecting, analysis, processing, and viewing. Data cleansing, missing value analysis, and outlier analysis are some of the opportunities and problems highlighted, in addition to the benefits and applications of big data. Outlier detection models, as well as methods for detecting and cleaning unclean data, were also suggested in this comprehensive review