Big Data Security Challenges

2014-12-24 03:37:28

There has been a lot of talk lately about the concept of “big data,” but big data is not really that new or novel.  It’s just standard data that’s usually distributed across multiple locations, from a diverse array of sources, in different formats and often unstructured.  Big Data comes with some of its own best practices and challenges, but even administrators with years of experience sometimes lose sight of the fact that they need to treat big data in much the same way they have always treated data.


The first challenges for big data were managing volume and assuring constant access. Now protecting data from intrusion and corruption, and maintaining secure access, are top priorities for tech professionals.


Davi Ottenheimer, senior director of trust for EMC, says a variety of methods should be evaluated and implemented in order to prevent data breaches.
Monitoring access


The complexity of big data environments means that audit trails can be lacking or even nonexistent, making it difficult to know which people accessed what information–and to determine what they did with it, says Ottenheimer.


“In many instances, everyone, even new hires, might be given full access to everything, increasing both intentional and accidental risk of damage,” says Ottenheimer. “Under these circumstances, it is likely to be impossible to determine who deleted all your data and how to prevent it in the future.”


Using analytics tools designed to analyze user behavior and spot abuse, access violations and other unintended actions can bring order and control to big data.


Multiple storage spots


Another challenge with big data is that it is typically stored in multiple places. This can make it difficult to verify that every part of the data is being accessed in response to a particular query.


Ottenheimer recommends using measures to ensure users get access to the data they need to do their jobs–and nothing more. However, if these rules are set incorrectly or introduce inappropriate limitations, the analysis delivered will likely be inaccurate.

If these concerns seem dramatic, they are no more so than protections needed for any sensitive data store. The difference is that so much attention has been devoted to the performance and collection of big data that the risks of access are sometimes overlooked. Employing the proper safeguards can go a long way toward enhancing both the short- and long-term value of even the largest collections of information.