5 Big Data Vulnerabilities You Could Be Overlooking

If a big data provider does not regularly update security for the environment or tools, it puts everyone else at risk for not just data loss but cyber attacks and major breaches.

You’re essentially trusting and relying on someone else to maintain the necessary systems.

While there’s no reason why they wouldn’t do this — and most providers are great at keeping up with such practices — it’s still a vulnerability that exists and will continue to exist.

You cannot force the big data owner or provider to properly maintain their systems, but you can stay informed.

Keep an eye on what’s happening, how long systems are out of date, and what that means for your own data and content.


Data Provenance Challenges Data generally contains more than just the basic information, it also includes historical records about the digital content, as well, and this is called data provenance.

In simpler terms, it’s a collection of metadata that reveals inputs, systems, entities and processes that have interacted with it.

Then there’s data lineage, which shows when content was accessed, by whom, if it was manipulated or edited and much more.

Often, the two concepts are considered to be the same thing.

Imagine just how massive a trove of metadata information truly is, as big data stores are huge on their own.

Each and every file, document or piece of data also contains a long list of descriptors and details about how it was influenced.

In terms of security, this additional metadata can cause a series of problems.

For starters, some details can be manipulated or changed, revealing false information or completely affecting how the data is organized and stored.

In addition, this information is not usually encrypted like the data contained within, which means snooping is possible.

This problem is tough to overcome, especially when you’re talking about visible details or information that is not encrypted or protected.

Using appropriate authentication and general security helps, as well as minding where the content is stored and how it’s made available to internal and external parties.


Lax NoSQL Database Security The high-speed and ever-evolving nature of NoSQL databases means that they’re constantly being adapted and revised.

Couple that with the fact that most NoSQL solutions are fairly new, meaning they’re in active development and modified by support teams too.

This creates several glaring vulnerabilities, as security is often mistreated altogether.

Most big data users hope that security is handled externally, and even trust that it’s happening.

That’s actually a big reason why administrative authentication is important, as mentioned earlier.

In reality, security is often ignored at a higher level, leaving the resulting data incredibly vulnerable.

Securing a database should always be a top priority, which calls for putting proper control and defense measures in place.

The four pillars of security are important here: authentication, authorization, auditing and encryption.

Pay attention to the security architecture of a system to ensure it both manages and deals with security properly.

If that’s not happening then you should either consider another system or another method, where applicable.

Who Is Responsible for Security?.Many security problems exist merely because the proper checks and balances are not in place, and nothing is done to ensure standards are being upheld.

It’s easy to fall into the trap of thinking that security should always be managed by a provider or big data owner, but no matter how much you trust a partner that’s just not a safe philosophy anyway.

The truth is that everyone is responsible for the security of a big data system and the data being stored, processed and exchanged by it.

From the owner to the users, everyone should understand what it takes to keep digital content secure.

And better yet, everyone should exercise the proper security measures be it applying encryption, or locking content access down to only select groups or individuals.

Adopting a proactive strategy is the best — and only — way to secure a big data solution.

About the Author Contributed by: Kayla Matthews, a technology writer and blogger covering big data topics for websites like Productivity Bytes, CloudTweaks, SandHill and VMblog.

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