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When relational database systems could no longer keep up with the huge amounts of unstructured data created by organizations, social media, and all other data-generating sources, big data came into being. The amount of data being added every day, together with Hadoop, makes for an urgent and growing need for more data processing solutions. The MapReduce programming model is one common approach for processing and handling huge amounts of data, especially when used to big data research. As HDFS, a distributed, scalable, and portable file system constructed in Java for the Hadoop architecture, is already useful, it is noteworthy that it is built using Java technology. This computing environment suffers from two issues. First, when intruders access the system, they can steal or corrupt the data stored in the system. The AES encryption mechanism has been implemented in HDFS to safeguard the security of data stored in HDFS. Some data saved in HDFS can be secured with the application of AES encryption technique. I conducted an extensive research on security challenges around large data in the context of Hadoop, along with numerous solutions and technologies utilized to secure it.

The world is becoming increasingly digital at the moment. Every day, a significant amount of data is generated by everyone who uses the internet nowadays. The data are critical for carrying out day-to-day operations, as well as assisting corporate management in achieving their objectives and making the best judgments possible based on the information gathered. BigData is the process of merging many hardware and software solutions to deal with extremely huge amounts of data that surpass storage capability. It’s possible that large amounts of data will be generated. Hadoop systems are used in a variety of areas, including healthcare, finance, and government. insurance, and social media, in order to provide a quick and cost-effective big data solution. The Apache Hadoop is a framework for storing and processing data, managing, and distributing large amounts of information over a large number of server nodes. Here are some solutions that work on top of the Apache Hadoop stack to guarantee data security. To get a complete picture of the problem, we decided to conduct an investigation into existing security solutions for Apache Hadoop security in sensitive data which is stored on a huge data platform employing distributed computing on a cluster of commodity devices. The goal of this paper is to provide knowledge of security and Big Data issues.

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