Data-centric security, at its heart, is just another lock. But what happens when that lock is picked (keys stolen, credentials compromised)? Over the coming quarters, effective monitoring and access analytics will become key to ensuring the success of this promising initiative.
We will see data-centric security becoming more and more relevant and essential over other forms of security. Network security can be compromised, however data security will prevent data that is hacked, from being read.
At the moment, data-centric security is receiving a great deal of attention. However, in higher-risk environments, there is resistance to implementation. This speaks to education and change management that goes beyond next several quarters.
Data-centric approach to security is a double-edged sword. Focus on protecting what needs to be protected can also lead to sprawling complexity if overdone. The best approach is to focus on as few classes of data as possible.
Data-centric security will continue to be a hot area, but the amount of data shown to human analysts will decline. It’s all about machines surfacing the interesting information.
The primary change within Data-centric security will be a trend toward developer targeted Platform-as-a-Service security solutions and away from costly and custom security hardware infrastructure.
As we move increasingly to cloud models, thus releasing control of infrastructure, security providers will focus more on the data itself and how we can manage, classify, and protect it.
In relation to data-centric security we excel at authenticating data users and data encryption, but first we need to go back to the basics of data discovery and classification.
The dual phenomena of cybercrime and big data make it critical that enterprises understand provenance, governance and data management as part of a holistic security story.