Why Do You Need a Data-Centric Security Strategy?

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Cloud and hybrid networks are the future of today’s fast-paced, online world. But using cloud-centric networks means that your data is constantly on the move. Worst, it could be moving across a network where you have little control over its security.

But what if you could put “armor” around your data? That way, it could stay protected regardless of where it goes or who accesses it. This principle is the core of how a data-centric security strategy works. 

What is Data-Centric Security?

Data- or information-centric security is a framework that sets up security policies around data protection. 

In this model, there is less emphasis on the location of the data (as with traditional models) and more focus on which data needs the most protection. Policies are created around the data to safeguard it from theft, compromise, or illegal access.

And because security is done at the data level, when the data moves, so will its protection. As a result, data-centric frameworks work best for cloud or hybrid networks where data moves a lot, and static cybersecurity measures are largely ineffective.

Data-centric approaches also treat applications as transitory – they are simply a “means to an end” so that users can work with the data. Thus, a data model is often developed first, with applications built around it.

The common approach with data-centric security is to use software agents as the “gatekeepers” that safeguard the data. These agents can be controlled from a centralized management platform. It’s also where administrators can set access privileges and permissions for each data type.

The Key Elements of a Data-Centric Security Framework
Data Discovery

A data threat-centric approach to protection starts with categorizing your data according to sensitivity and use case. This process is called a data discovery audit. It should tell you every piece of data in your entire network, including on cloud servers.

Knowing this data is crucial because every data requires different approaches and levels of protection. 

Access Management

This forms the core of your data-centric security strategy. Effective access management ensures that only users with the right privileges can access the appropriate data for them. This is enforced via authentication and authorization algorithms.

A key principle here is to assign data on an “as needed” basis. In other words, users should only be exposed to the data needed to perform their task and nothing more.

Data Protection

These are the security safeguards in place that help secure your data, whether it’s at rest or in transit. A data-centric encryption protocol is one of the most important aspects of data protection. Data loss prevention (DLP) is also vital for continually monitoring sensitive data to ensure it’s not at risk.


Compliance with data regulations in your country is paramount if you want to avoid penalties. That’s why effective governance is important. You can stay compliant by performing audits and constantly training your in-house data security team. 

Why a Data-Centric Security Strategy Matters
Automated data protection

A data-centric security approach helps automate data protection by automatically scanning whenever a file is added or modified in the network. Depending on the data type and classification, the system will then assign a policy based on its protection level.

This is done in the background, allowing minimal room for human error.

Protects data in case of a breach

Data-centric security provides a robust defense on its own, even when the network itself is already breached. Thus, it can prevent hackers from getting their hands on sensitive data. This can allow for faster disaster recovery, reduce risk, and minimize the impact on your operation.

Mobile and flexible protection

The most significant pro with data-centric security is that the data itself is protected instead of the server or network it’s in. And it will carry that protection regardless of who interacts with it or which device or system it’s located within.

How to Implement a Data-Centric Security Strategy

Data is the most important asset in any data-centric security system, so it makes sense to start there. Begin by gathering all the data in your network, then auditing them based on usage. Which applications are using it? Does it contain sensitive data? How can I protect it?

Classifying data enables you to think of protocols to protect them. After all, the way you’ll safeguard credit card information will be radically different from how you’ll treat medical records.

Next, identify the users who need to access this data. Assign each a role together with access privileges to the data. But it’s not a “set it and forget it” thing – you should have a plan to constantly re-assess these user accounts.

Once you have access privileges set, you should look into data-centric information security technology. Limited protection of data while in transit is also a key consideration here, so implement encryption algorithms like Pretty Good Privacy (PGP).

The final strategy that will bring your data-centric approach to its maximum is a data governance plan. Having the processes in place to control and track data flow is crucial if you want to know where everything is at all times.

TokenEx and Data-Centric Security

The TokenEx platform can help you establish a data-centric security strategy by providing a seamless PCI compliance tool for accepting, storing, and transmitting sensitive data.

How to Choose
a Tokenization Solution

Make sure you’re asking the right questions by reading this resource.