Data Classification Use Scenarios

Data Classification is directly related to risk management, compliance, and protection against internal threats. Organizing structured and unstructured data into appropriate categories ensures efficient use and data protection across the company network. With no data classification in place, any data protection program will fail. Here’s what Data Classification can help you with:

• Mitigate risks. Gain control over location and access to sensitive information, thus reducing possible threats.

Zecurion DLP doesn’t use document tags as this technology is unreliable: labels may not reflect the actual content.

• Optimize business processes. Manage efficient access to work-required data by approved users, discover and eliminate redundant data, optimize business activities.

Zecurion DLP checks the content of documents in motion each time a policy is applied. It’s more complicated but more valid. Our next-generation technologies ensure these checks work instantly without slowing down the system.

• Comply with regulations. After identifying data governed by applicable regulations, you can put additional tracking or control measures. You can also enable quarantine, archiving, or other regulation-required actions.

Zecurion DLP has its own pre-installed data classification tools. You will not require third-party solutions to ensure the data are under control.

Data Sensitivity Levels

The United States government has seven levels, classified from the most minor “Controlled Unclassified Information (CUI)” to the most sensitive “Restricted Data/Formerly Restricted Data.” This number of levels can be overabundant for most organizations, whereas a system with three-four levels will exclude complexity and be easier to maintain. We suggest keeping it simple.

• High sensitivity data: information that, if made public, could cause significant harm to an individual or the organization, can potentially lead to financial and reputational losses, or pose a risk to company operations.
• Medium sensitivity data: intended for internal use only but is not sensitive, such as construction plans, marketing strategies, etc.
• Low sensitivity data: data created for public access. Examples include product datasheets, webpages, blogs, etc.

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