Security cannot be an afterthought when developing and deploying Big Data commercial applications. If you must ask whether your big data applications are secure, the answer is probably no. What’s the answer? Mitigating risks and ensuring security requires the ability to leverage existing identity infrastructure, control access privileges, and conduct user-level audits.
Commercial applications are increasingly available on Big Data infrastructure, allowing the enterprise to leverage extremely large data sets to swiftly curate, manage, and process information. But it’s crucial to address the potential security risks inherent in processing such large volumes of data.
Big Data applications housing sensitive and personally identifiable information (PII) are typically governed by corporate security and regulatory compliance policies. Least-privilege access should be granted only to users who need access to these resources to perform their jobs.
The enterprise also needs to control access, manage privileges, audit activities, and associate all access activities back to an individual. This allows you to mitigate threats resulting from identity-related risks while successfully addressing audit and compliance requirements.
For example, by deploying the Centrify Server Suite, the enterprise can leverage existing Microsoft Active Directory infrastructure to standardize Big Data cluster operations. IT can secure and simplify Big Data environments at the operating system layer without deploying and managing new identity infrastructure. You can also increase security by implementing privileged identity management solutions for leading Big Data environments, such as Apache Hadoop as well as Big Data solutions from Cloudera, Hortonworks, and MapR Technologies.
Enabling simplified and secure access
The enterprise can benefit from simple and secure access to these Big Data environments, and leverage Active Directory to avoid the hassle of introducing alternative solutions that do not scale and require additional training for IT.
Implementing single sign-on (SSO) for both IT administrators and Big Data users allows you to further extend the power of Active Directory’s Kerberos and LDAP capabilities to Big Data clusters. By adding SSO functionality to Big Data environments, you can make users more productive and secure by allowing them to log in as themselves, rather than having to share privileged accounts.
Tracking user activities and documenting compliance with regulatory requirements and enterprise policies also reduces identity-related risks. Deploying an identity management solution that can track user activity and associate it with an individual in Active Directory therefore helps the enterprise make Big Data more secure.
By enforcing access controls and least-privilege security across Big Data infrastructure, the enterprise can also benefit from cost-effective compliance through combined access and activity reporting.
For additional information on how to make sure that your big data commercial applications are secure, download the How Identity Management Solves Five Hadoop Security Risks whitepaper.