Big Data Privacy for end to end Delivery
Ashutosh Dixit1, Nidhi Tyagi2

1Ashutosh Dixit, Research Scholar, Bhagwant University, Ajmer (Rajasthan), India.
2Dr. Nidhi Tyagi, Professor, MIET, Meerut (U.P), India.
Manuscript received on 22 August 2019 | Revised Manuscript received on 11 September 2019 | Manuscript Published on 17 September 2019 | PP: 1563-1566 | Volume-8 Issue-2S8 August 2019 | Retrieval Number: B11040882S819/2019©BEIESP | DOI: 10.35940/ijrte.B1104.0882S819
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Abstract: Data privacy is an area of concern to process massive datasets in Big Data applications. Assortment of Big Data-sets is tough to be handled using, with the use of on-hand management tools or traditional processing techniques, the assortment of Big Data sets is difficult to be handled using Big Data has three characteristics i.e. V’s Volume, Varity, and Velocity . Privacy to such Big Data could be a massive snag which might be achieved by Anonymization technique. Datasets like financial data, Health Records and other confidential information of various organizations needs privacy to protect from the intruders and malicious entities. The aim of Big Data Anonymization is to shield the privacy of the individual and make it legal to share the information while not obtaining permission from people. The research paper discusses the basics of Big Data, technology behind it and various challenges.
Keywords: Big Data, Hadoop, HDFS, Map Reduce, Data Anonymization, Kerberos Security System.
Scope of the Article: Big Data Analytics and Business Intelligence