BibTeX:

@article{IJIRSTV5I10023,
     title={Security and Challenges in Big Data: A Survey},
     author={Jignesh Solanki, Vijaysinh Jadeja, Chirag Patel, Shaktisinh Parmar and Sohil Gadhiya},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={5},
     number={10},
     pages={61--63},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV5I10023.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

The big data explosion has given rise to a host of information technology tools and capabilities that enable organizations to capture manage and analyze large sets of structured and unstructured data for actionable insights and competitive advantage. But with this new technology comes the challenge of keeping sensitive information private and secure. Big data that resides within a Hadoop environment can contain sensitive financial data in the form of credit card and bank account numbers. It may also contain proprietary corporate information and personally identifiable information (PII) such as the names, addresses and social security numbers of clients, customers and employees .Due to the sensitive nature of all of this data and the damage that can be done should it fall into the wrong hands, it is imperative that it be protected from unauthorized access. To that end, here is a look at some common Hadoop security issues along with best practices to keep sensitive data safe and secure.

Big Data, Hadoop, HDFS, ETL, Map Reduce