Authorization of Data In Hadoop Using Apache Sentry

  • Authors

    • N Sirisha
    • K V.D. Kiran
    https://doi.org/10.14419/ijet.v7i3.6.14978

    Received date: July 2, 2018

    Accepted date: July 2, 2018

    Published date: July 4, 2018

  • Hadoop, apache sentry, security, TDE, encryption zone, knox, ranger.

  • Abstract

    Big Data has become more popular, as it can provide on-demand, reliable and flexible services to users such as storage and its processing. The data security has become a major issue in the Big data. The open source HDFS software is used to store huge amount of data with high throughput and fault tolerance and Map Reduce is used for its computations and processing. However, it is a significant target in the Hadoop system, security model was not designed and became the major drawback of Hadoop software. In terms of storage, meta data security, sensitive data  and also the data security will be an serious issue in HDFS. With the importance of Hadoop in today's enterprises, there is also an increasing trend in providing a high security features in enterprises. Over recent years, only some level of security in Hadoop such as Kerberos and Transparent Data Encryption(TDE),Encryption techniques, hash techniques are shown for Hadoop. This paper, shows the efforts that are made to present Hadoop Authorization security issues using Apache Sentry in HDFS.

  • References

    1. Sirisha N & Kiran KVD, “Protection Of Encroachment On Bigdata Aspects”, International Journal of Mechanical Engineering and Technology (IJMET), Vol.8, No.7, (2017), pp.550–558.
    2. Park S & Lee Y, “Secure Hadoopwith Encrypted HDFS”, Springer-Verlag Berlin Heidelberg, (2013), pp.134–141.
    3. Dean J & Ghemawat S, “MapReduce: simplified data processing on large clusters”, CACM, Vol.51, No.1, (2008), pp.107-113.
    4. Park S & Lee Y, “Secure hadoop with encrypted HDFS”, International Conference on Grid and Pervasive Computing, (2013), pp.134-141.
    5. Zerfos P, Yeo H, Paulovicks BD & Sheinin V, “SDFS: Secure distributed file system for data-at-rest security for Hadoop-as-a-service”, IEEE International Conference on Big Data (Big Data), (2015), pp.1262-1271.
    6. Grover C & Aulakh MK, “Big Data Authentication and Authorization in HDP (Hadoop Distributed platform) using Kerberos and Ranger”, 2nd International Conference on Recent Innovations in Management and Engineering, (2017), pp.44-51.
    7. Cheng Z, Zhang D, Huang H & Qian Z, “Design and Implementation of Data Encryptionin Cloud based on HDFS”, International Workshop on Cloud Computing and Information Security, (2013), pp.274-277.
    8. Shehzad D, Khan Z, Dag H & Bozkus Z, “A novel hybrid encryption scheme to ensure Hadoop based cloud data security”, International Journal of Computer Science and Information Security, Vol.14,No.4,(2016).
    9. Rabin MO, “Efficient Dispersal of Information for Security, Load Balancing, and Fault Tolerance”, Journal of the Association for Computing Machinery, Vol.36, No.2, (1989), pp.335-348.
    10. "Transparent Encryption in HDFS.
    11. https://hadoop.apache.org/docs/r2.7.2/hadoop-project dist/hadoophdfs/TransparentEncryption.html.
    12. Byers J, Luby M, Mitzenmacher M & Reg A e, “A Digital Foundation Approach to Reliable Distribution of Bulk Data”, Proc.ACM SIGCOMM’98, Vol.28, No.4, (1998), pp.56-67.
    13. Darade SA & Kamble K, “Network Level Security in Hadoop Using Wire Encryption”, International journal of Advanced research in science management and technology,Vol.1, No.6, (2015).
    14. Cloudera Inc., “HDFS Data At Rest Encryption”,
    15. http://www.cloudera.com/content/cloudera/en/documentation/core/latest/topics/cdh_sg_hdfs_encryption.html#xd_583c10bfdbd326ba--5a52cca-1476e7473cd--7f85, 2015.
    16. IBM BigInsights on Cloud, IBM, 2016.
    17. http://www-03.ibm.com/software/products/en/ibm-biginsights-oncloud.
    18. Vivekanand & Vidyavathi BM, “Security Challenges in Big Data: Review”, International Journal of Advanced Research in Computer Science, Vol.6, No.6, (2015).

  • Downloads

  • How to Cite

    Sirisha, N., & V.D. Kiran, K. (2018). Authorization of Data In Hadoop Using Apache Sentry. International Journal of Engineering and Technology, 7(3.6), 234-236. https://doi.org/10.14419/ijet.v7i3.6.14978