How to build a robust data-centric security strategy with automation

For effective data security, it is critical to reduce user intervention and provide an unbiased monitoring system.

How to build a robust data-centric security strategy with automation

Sunday February 19, 2023,

4 min Read

Of later, there has been exponential growth in data volume due to the growing use of technologies like software-as-a-service (SaaS), infrastructure-as-a-service (IaaS), and platform-as-a-service (PaaS) in the last couple of years. Today, data flows from devices to on-premise systems, and cloud applications to third-party vendors and business partners making them effectively omnipresent.  

With this, accompanies several technical, legal, and process-related challenges. Traditional perimeter security systems rely on many hand offs—that is from device security to network security to application security and then back to device security for a document being sent via email.

Meanwhile, the looming threat of data breaches, compliance mandates, cloud adoption requirements and rapidly changing threat landscape remain—creating  the perfect storm for security to become more data centric.

Time-to-value is rapidly becoming a critical evaluation criteria as enterprises and their security teams lose patience. Security solution providers are therefore focussed on removing any step that requires human involvement. Successful data security projects are therefore ones where activities like deployment, IT administration, policy creation and even user participation have been automated away management overheads can be eliminated.

Ensuring automation at every step

Through deployment automation , companies with modern container based infrastructure can reduce and in some cases remove traditional deployment overheads. Any serious enterprise security system will use these techniques to go live in under 24 hours. Another option is admin automation—which

enables a company to address business dynamics like onboarding new hires, departing employees, transfers, and external collaboration more efficiently. Using automation and artificial intelligence, platforms can be automated to audit the process with prebuilt analytics. Active data usage tracking is possible with systems like Digital Rights Management (DRM) solutions that include auditing capabilities. This increases a firm’s security teams' awareness of sensitive data use and provides a better context for unauthorised activities, allowing them to make well-informed policy decisions.

To get users on the same age about sensitivity of a  data asset, visibility automation is key.  It is possible for users to assign data security policies incorrectly. According to the IDC's Data Protection and Privacy Survey 2021, many organizations applied stringent security policies to data that did not require it. They did not, however, use any security policies for sensitive data such as intellectual property, contracts, research data, and so on.

While manual data protection is prone to errors and false positives, automation eliminates or at least reduces the possibility of such errors. By removing the user from the context and answering the question "What to protect?" through automation using inputs from other data-focused solutions, the system gains consistency. This visibility can be used to automate the job of searching and classifying confidential data for the enterprise.

In the past, managing an organization's security policies was a manual process that necessitated extensive administrative intervention, impacting operational efficiency of the organizations. Enterprises have already deployed many tools which incorporate the enterprise information security policies. These tools can be as diverse as an enterprise resource planning system to a file-based collaboration system.

Security policies incorporated within these systems can be used seamlessly to protect data and any data centric security system should have a method of federating these security policies. Furthermore, automation assists an organization in dealing with ever-changing privacy requirements to ensure compliance and the ease of policy updates.

What are the benefits of Automation of data centric security?

Automation in the context of data centric security has a lot of benefits beyond time to value. By automating deployment, policy administration and visibility, the administrative overhead of managing a system and the requirement of security talent goes down drastically. This results in lower operational costs.

It can also result in reduction of overhead costs, by removing the need for end user participation, the overheads of training, enablement and process changes related to end user, which inturn reduces operational costs.

Any system which depends on people to deploy, administer, and use the system inherently suffers from scalability limitations. Automation removes these scalability limitations and allows the system to be used to it full capacity.

When it comes to managing complex data security and privacy systems, it has been widely observed that the weakest links are the people—namely its admins and users. For effective data security, it is critical to reduce user intervention and provide an unbiased monitoring system. Taking the user out of context and automatically protecting data at the source through integration with other security tools, mail and messaging systems, or storage and collaboration systems will enable enterprises to successfully implement and adapt their data security initiatives.

(Vishal is the Founder and CEO of Seclore and oversees the company’s corporate development, investor relations, and strategic vision.)

Edited by Akanksha Sarma

(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory.)