How to protect data throughout its lifecycle

Data changes, is exchanged and further processed. Protecting it throughout its entire lifecycle is not so easy. The following article shows which steps are required.

There are four main steps to protecting data throughout its lifecycle. (Image: Unsplash.com)

On average, it takes companies more than a month to detect and remediate security breaches. Yet data can be reliably protected if you consider its complete lifecycle - from creation to deletion. Forcepoint, a provider of IT security solutions for enterprises and public administrations, has found that these four steps are crucial:

  1. Data Discovery: The first step is to track down all of the company's data. Typically, data is scattered across countless endpoints, servers and cloud services, so the challenge is not to miss any storage locations. The goal of data discovery is to find out what data the company even owns, where it is stored, who can access it, and when it was last accessed. Users often have more access rights than they actually need. Assigning rights according to the least privilege principle helps to minimize risks because users only receive the authorizations they need for their activities. In addition, knowledge of one's own data is necessary for compliance with regulatory requirements and standards such as DSGVO or PCI DSS. After all, companies cannot protect sensitive data if it is hidden in unknown storage locations or in a huge mountain of dark data.
  2. Data Classification: Once all the data has been collected, the next step is classification, i.e. division into categories. Based on this, companies can define appropriate protection for each category and prioritize the most sensitive data. However, given the enormous volumes of data in most companies, manual classification is extremely time-consuming and error-prone, if not impossible. Advances in AI and machine learning, however, now allow fast and accurate automated classification. This not only flags data that is particularly worthy of protection, but also data garbage, for example. This is redundant, obsolete and trivial information that is simply superfluous and can be deleted. This saves costs and reduces risks.
  3. Data Monitoring: Tracking down and classifying data is just the beginning, because comprehensive protection also requires continuous monitoring. On the one hand, to keep the information about the data stock up to date - after all, data is constantly being copied, processed and transferred. On the other hand, to identify potential threats and quickly initiate countermeasures to stop data leakage or data breaches. Real-time monitoring of all data, storage systems and accesses helps to identify unusual changes to data, accesses that deviate from normal access patterns and other suspicious activities. This information is important for risk assessments and enables proactive responses. It also feeds into reports and audit trails, enabling organizations to demonstrate their security efforts and track the progress of security breaches in detail.
  4. Data Protection: Data discovery, classification and monitoring provide valuable information on which companies can build to largely automate the protection of their data. The key is a data-first approach that allows control of all interactions with the data and the reliable enforcement of policies. These policies should be able to be managed consistently and centrally to avoid inconsistencies and thus gaps in protection that often occur when each tool brings its own set of rules. Moreover, many dangers can be massively reduced by Zero Trust, because, for example, infected files do not enter the company in the first place or cyber criminals do not even reach the valuable data thanks to restrictive assignment of rights and consistent authentication of all accesses.

"Ultimately, companies can only protect their data if they know it and know what is happening to it," emphasizes Frank Limberger Data & Insider Threat Security Specialist at Forcepoint in Munich. "That's why it's not enough to just capture and classify data once. Rather, companies need modern technologies and solutions that continuously watch over all data and offer a high degree of automation. Today's data inventories are simply too large for manual work - moreover, security breaches require immediate reactions, because when data leaks or is encrypted, every second counts."

Source and further information: Forcepoint

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