Historically, Apache Hadoop has provided limited security capabilities, and most Hadoop implementations to date have been deployed with little thought given to security. To protect sensitive data being stored and analyzed in Hadoop, security architects should use a structured approach to security as recommended in one of Gartner’s recent research report.

1. Best Practices for Securing Hadoop
Historically,Apache Hadoophasprovidedlimitedsecuritycapabilities,andmostHadoop
implementationstodate have beendeployedwithlittle thoughtgiventosecurity.Toprotectsensitive
data beingstoredandanalyzedinHadoop,securityarchitectsshoulduse astructuredapproachto
securityasrecommendedinone of Gartner’srecentresearchreport.
Source: Gartner
Source: Gartner

2. Take a Life Cycle Approach to Securing Data in Hadoop
Data has a lifecyclewithin an organization.Itis typically created within enterprise systems,and duringits life
cycle,it may go into and out of Hadoop and other big data repositories,as well as into backup and archival
systems. Viewed in this way, the Hadoop protection strategy cannotbe limited to the protection of only the data
within Hadoop discussed thus far.
A best practiceis to take a data life-cycle-centric approach to the security within Hadoop that considers these
issues:
 How and when is data loaded into Hadoop? Which users,groups and systems have rights to do this? If the
data loads areprogrammatic,what controls (such as certificate-based authentication) protect
programmatic access? Whatsteps are taken to ensure the integrity and authenticity of the data being
loaded?
 If sensitivedata is loaded,has itbeen anonymized where necessary?
 Are end-user or automated extracts from Hadoop prevented? Or, if allowed,how is the extracted data
protected? At a minimum, these activities should belogged usingDAP solutions described in this
research.
 Is data backed up from Hadoop? Is so,are these backups encrypted? Who has access to the backups?
 Is data archived from Hadoop? If so, how are these archives protected?
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