A data loss prevention (DLP) strategy is crucial to protecting your organization’s sensitive data. Unfortunately, many organizations overlook the importance of protecting data at rest and instead focus their resources to protect data during other stages of its lifecycle. These gaps in security can lead to data breaches, data exfiltration, and other scenarios that can result in significant financial and reputational harm. Here’s what you need to know about data at rest, and why your organization’s DLP strategy needs to account for sensitive data no matter where it lives.
What is a DLP strategy?
A comprehensive DLP strategy includes all of the programs and processes used by an organization to protect sensitive information from theft, loss, or misuse. A well-planned DLP strategy can protect sensitive information to mitigate risks to your organization.
At the same time, a DLP strategy needs to be conducive to productive business, and employees must be able to conduct daily work tasks without undue burden. Your organizational strategy needs to provide risk-appropriate protections. Failure to take this factor into account can lead to employees seeking workarounds or committing unnecessary errors. Considering human error is the leading cause of insider data breaches, an ineffective DLP strategy can be as harmful as no strategy at all.
How a DLP strategy protects your assets
DLP is more than just a single piece of software. Your organization’s approach to data security and consumer privacy protection should include a full deck of tools and security policies designed to prevent, detect, and remediate data loss, theft, and leakage. Additionally, your DLP strategy should protect data during all three stages of the data lifecycle: data at rest, data in motion, and data in use. While data at rest may eventually be moved (thereby becoming data in motion) or accessed (data in use), focusing solely on the latter two states positions your organization as reactive rather than proactive.
Data at rest
Data at rest refers to the information stored in your organization’s databases, on servers, and on endpoint devices. The best way to protect this data is through automation and persistent metadata tagging. Unfortunately, many organizations rely solely on manual or semi-automated tagging and classification, to the detriment of their overall data security.
Alternatively, automated data classification allows organizations to properly classify data to better understand the full scope of the data under their control. When paired with accurate data discovery, your organization can draw a more complete picture of the information in your control.
Data in motion
Data actively being moved from one location to another is called data in motion or data in transit. Uploads and downloads to the cloud, movement from shared drives to personal drives, and similar data moves present a unique security risk to organizations. Though the least common state of data, data in motion is nonetheless the most vulnerable state. Any time data moves from protected internal storage systems to an outside party or agency, the potential for a security breach is at its highest.
The key to securing data in motion is to secure data at its source. Through proper classification, access controls, encryption, and monitoring, you’ll be better able to protect your data before it’s moved.
Data in use
The “gold standard” for protecting data is a Zero Trust framework. This approach to data security requires user identities to be verified every time they attempt to access sensitive information and provides the greatest level of protection for your data. It’s for this reason that your DLP solution should protect data using a Zero Trust model.
Creating a comprehensive DLP strategy
Only by securing data at rest can your organization claim a data-centric approach to security. Without securing data where it lives in your systems, your organization remains exposed to both internal and external threats.
Instead, by properly securing data at rest, your organization can adopt a proactive approach to security rather than a reactive one. By creating access policies that adequately cover your users and workflows at the data level, prevention systems can be triggered at the time of attempted access rather than monitoring changes and attempting to backtrace loss to the source. You’ll also have a more granular view of the specific data being accessed by a given party, resulting in a greater level of detail should a breach need to be reported.
How the Spirion Governance Suite can address your DLP needs
Spirion’s Governance Suite provides a full selection of tools to help your organization create a data loss prevention strategy capable of standing up to the data security threats faced by modern businesses. With the Governance Suite at your disposal, you’ll have a better understanding of the sensitive data you possess as well as the tools you need to properly classify and monitor that data.
With cybercrime predicted to cost the world upwards of $10.5 trillion by 2025, failure to adequately prepare your organization can result in significant financial damage to both you and your customers. See for yourself how Spirion can help you build a customized DLP strategy for your business by scheduling a product demo or contacting us for more information.