Data Loss Prevention
Learn how DLP prevents unauthorized data exposure and compliance violations.
Data loss prevention (DLP) refers to a class of security solutions that identify and prevent data exposure risk or the inappropriate sharing, transfer, or use of sensitive data. DLP accomplishes this by looking at the content of data (i.e. credit cards, social security numbers, or other PII and PHI) through data classification. More sophisticated types of DLP will also evaluate file metadata to take into account details like who created the data, which roles have access to the data, as well as where data is ingressing from or egressing to in order to help evaluate data exposure risk.
Resource Center
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The Top 10 Data Loss Prevention Software Products -
What happened to the Gartner Data Loss Prevention Magic Quadrant? -
Forcepoint DLP Competitors and Alternatives -
Digital Guardian DLP Competitors and Alternatives -
The Top 5 DTEX Alternatives and Competitors 2023 -
The Top 5 Symantec DLP Alternatives and Competitors in 2023 -
The Top 5 McAfee DLP Alternatives and Competitors 2023
What Does Data Loss Prevention Protect Against?
DLP is intended to prevent multiple worst case scenarios for your organization's data to ensure legal compliance and security
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Unintentional Exposure of Sensitive Data
Employee security violations are usually unintentional and accidental, with multiple studies finding that the vast majority of data breaches result from human error. DLP is intended to monitor for violations of your data security policies and best practices and correct these behaviors in the background to demonstrate regulatory compliance and reduce your breach risk.
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Egress of Sensitive Data into Unsanctioned Apps
In order to keep productivity up, employees may seek out new tools and platforms, like ChatGPT, for example. If these applications and services aren’t sanctioned or provisioned by your organization’s IT, you can have sensitive data flowing into environments where you have no visibility. DLP can provide visibility into this data and even prevent it from going into unsanctioned apps in the first place.
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Exfiltration of Sensitive Data
Some instances of data loss result from intentional or deliberate attempts to move data. Individuals who exfiltrate data might be departing employees, who are leaving for a competitor, employees who want to work off of non-sanctioned devices, or in a worse case scenario active threat actors.
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Abuse of Sensitive Data
Sometimes malicious behaviors stem from employees who have need-to-know access to sensitive information like credit card numbers or social security numbers, that decide to violate stakeholder trust by abusing this information. Sophisticated DLP can determine when someone who is authorized to access data is using it in an impermissible manner.
How does data loss prevention work?
There are many different types of data loss prevention, with some only specializing in scanning SaaS applications or endpoints exclusively for data leakage. Modern and comprehensive data loss prevention solutions work by:
- Integrating with core pieces of infrastructure at the endpoint layer, like the device’s operating system and browsers to monitor data ingress and egress occurring on the device without having to decrypt traffic leaving the device to perform content inspection.
- Leveraging APIs to integrate with core cloud services and applications in use by an organization.
- Monitoring file operations at both the endpoint and cloud layers, to use this metadata to provide critical context about which pieces of data are business-critical or at highest exposure risk.
Learn more about modern approaches to data loss prevention here
Read Gartner's Market Guide for DLP
Learn more about the modern approach to DLP
Addressing the Top 5 Gaps in DLP
Cloud adoption and work-from-home trends are stressing legacy DLP solutions. Learn how you can address the most common weaknesses in data security programs for hybrid workforces.
Data security reimagined: beyond DLP and insider risk
