The importance of protecting sensitive data at rest
Data is constantly on the move across enterprises, and because of this, data security strategies are often an amalgamation of tools, platforms, and policies focused on keeping sensitive information safe while in motion. But, that data has to rest eventually, and whether that happens on employee endpoint devices, networks, or the cloud, it needs to be protected in this state as well.
Why? Because despite data in motion being thought of as most vulnerable to threats, data at rest is actually the more frequent target. Unauthorized outsiders and malicious insiders can both recognize the value of targeting data at rest—it can be stolen in higher volumes, which equates to a higher reward.
How data classification protects sensitive data at rest and beyond
Through the foundational step of data classification—whereby sensitive data files are categorized with context-rich metadata tags that identify level of sensitivity, purpose for collecting the data, business processes, applicable regulatory guidelines, custom criteria, and more—data at rest can receive the degree of protection it requires.
The added bonus of classification with persistent tagging is that these tags follow data when it begins to move, wherever it goes, so it can be secure in transit, as well as its next resting location. When data is inevitably modified as it’s processed, its tags are updated to provide the most up-to-date context. Moreover, when data encounters other tools in your security stack as it moves, such as those for enforcing access controls, encryption, or data loss prevention, its standardized tagging schema allows these tools to easily understand the data they’re dealing with, enabling them to work at maximum efficacy.
Take DLP tools, which protect and remediate sensitive data they’ve identified after searching for it based on predefined terms, file names, and compliance regulations. If that data were to be wrongly labeled, or not labeled at all, it could be mishandled or disregarded by a DLP tool. With metadata tags attached to sensitive data that provide detailed context, DLP tools can effectively execute their duties within organizations’ greater security strategies.
Understanding how data tagging tools enhance security
A data classification tool possesses tagging capabilities based on predefined fields, while also offering organizations the ability to create custom fields. One of the primary benefits of a data classification tool is its ability to eliminate risks stemming from human error, so it’s important for organizations to adopt uniform naming conventions. That way, even custom tags can be understood by other platforms in your security stack.
As soon as a piece of data— structured and unstructured—enters your environment, it’s discovered and classified with tags that put this sensitive information into context. From here, role-based security controls based on internal security policies and compliance rules can be applied to data. It can also be securely stored, moved, and used in accordance with the aforementioned governance rules, and properly disposed of in a timely, compliant manner. And, there’s the monitoring component to consider as well. With tags defining how data can be used and by whom, abnormal behavior involving the data or unauthorized access to it can be caught quickly by security teams for a swift response.
Fortify your data security approach with Spirion’s automated data classification tool
Spirion offers highly accurate, automated data classification with persistent tagging so sensitive data can be secured as soon as it enters your organization’s environment. With context-rich labels that are easily understood by other tools in your security stack, you’re able to feel confident that your data is secure both at rest and in motion. As it moves, it can be monitored to ensure it sticks to your organization’s internal security policies while also maintaining compliance with the strictest of privacy regulations.
Contact us today to learn how our scalable solutions can help strengthen your data-centric security approach, make business operations more efficient, and reduce risk within your environment.