Ensure Security for Mapreduce-Hadoop Distributed File System using Encryption Method Over Big Data
Gunjan V. Keswani

Gunjan V. Keswani, Department of Computer Application, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India.
Manuscript received on 06 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 733-740 | Volume-8 Issue-10, August 2019 | Retrieval Number: J88830881019/2019©BEIESP | DOI: 10.35940/ijitee.J8883.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Big data security is the most focused research issue nowadays due to their increased size and the complexity involved in handling of large volume of data. It is more difficult to ensure security on big data handling due to its characteristics 4V’s. With the aim of ensuring security and flexible encryption computation on big data with reduced computation overhead in this work, framework with encryption (MRS) is presented with Hadoop Distributed file System (HDFS). Development of the MapReduce paradigm needs networked attached storage in addition to parallel processing. For storing as well as handling big data, HDFS are extensively utilized. This proposed method creates a framework for obtaining data from client and after that examining the received data, excerpt privacy policy and after that find the sensitive data. The security is guaranteed in this framework using key rotation algorithm which is an efficient encryption and decryption technique for safeguarding the data over big data. Data encryption is a means to protect data in storage with containing a key encryption saved and accessible to reuse the data while required. The outcome shows that the research method guarantees greater security for enormous amount of data and gives beneficial info to related clients. Therefore the outcome concluded that the proposed method is superior to the previous method. Finally, this research can be applied effectively on the various domains such as health care domains, educational domains, social networking domains, etc which require more security and increased volume of data.
Keywords: Big data, security, Hadoop, MapReduce, encryption
Scope of the Article: Big Data Analytics