Initially, Hadoop framework was developed without keeping security in mind. But later it is observed that without security, data is at high risk. The trustworthiness of data sources is necessary to be proved. Technologies must be explored for identifying security threats in Big data. There have been a lot of issues and challenges (Jaseena et. al. 2014; CSA, 2012) related to the security in the Big data and Hadoop framework which are as follows:

  • • Unauthorised access of information in Hadoop environment.
  • • Execution of arbitrary code by attackers.
  • • Illegal read/write of a data block of any file in Hadoop.
  • • Eavesdropping or sniffing to data packets being sent to users.
  • • Unauthorised access of privileges to change priority of job, delete, modify or submission of any malicious job to a queue.

There are some conceptual points which focus on the security requirements of Big data. These points must be understood by the enterprises and organizations to implement some efficient technologies for creating a secure Big data environment. [1]

  • • It is important to secure data storage and transaction logs with real-time security monitoring and end-point input validation.
  • • Automated data transmission needs extra security, which are probably not present in Hadoop framework.
  • • It is also required to validate the trustworthiness and accuracy of information on receiving large quantity of data by a system.

  • [1] Big data must not compromise its essential characteristics i.e. volume, velocity, variety. • It should not compromise the elementary technology and functionality of theHadoop clusters. • It must alert about security threat to Hadoop environment or data stored within the blocks. • It should address the three kinds of security violations: unauthorised releaseof information, variation of information and repudiation of resources. • Secure computation is the main requirement in distributed programmingframework for Big data.
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