Big Data Privacy and Security in Data Analytics: A Review On Issues, Challenges and Privacy Preserving Methods

Abstract

In recent years, with the rapid development of technologies such as the internet, the internet of things and cloud computing, data production has increased in many areas such as business, education and economy. Big Data has emerged as a prominent concern of interest international, drawing huge attention throughout these fields. However, making sure the privateness and safety of Big Data stays a vital difficulty. The specific 5V traits of Big Data—Volume, Variety, Velocity, Value, and Veracity—demand stronger security measures to deal with those demanding situations efficiently. This studies paper highlights key security and privateness concerns related to Big Data as recognized by means of the Cloud Security Alliance (CSA). It also explores potential techniques and answers to beautify the safety of facts processing and computing infrastructures. Additionally, the paper gives a top-level view of the K-Anonymity method, a privacy-preserving technique designed to guard character identities and touchy records from being disclosed when datasets are shared or analyzed. Finally, the observe reviews Big Data safety solutions provided by using leading companies and outlines their features to ensure robust statistics safety.