What are Data Classification Levels?

Every organization uses data to some extent. Whether it’s public information about the company, internal procedures for employees or financial forecasts for the next few years, it’s important to know who has access to that data and how that data is being used. In this article, we’ll look at how Data Classification can help you make the right decisions to protect your most sensitive data.

What is Data Classification?

Not every bit of organizational data requires top-level security, and in order to assign the right kind of security to the most confidential data, it’s important to classify it. Data classification is also vital for several compliance standards.

Not every bit of organizational data requires top-level security, and in order to assign the right kind of security to the most confidential data, it’s important to classify it. Data classification is also vital for several compliance standards.

4 Common Classification Levels

There are four main classification levels in most organizations.

• Public:

This data is available to the public and is available on an open website or discussed in seminars or other events. Public information is usually general information about a company or its products. It is not sensitive or controversial in nature.

• Internal:

Internal data is data that’s known to its employees. Documents such as office memos are not available to the general public, but if they’re leaked, they don’t usually pose a risk to the organization.

• Confidential:

Confidential data is available only to small teams in an organization. This data should be kept within that team, and if it’s leaked, it can have some negative financial or reputational impact on the business.

• Restricted:

Restricted data is the most sensitive in nature and can have a serious financial or reputational impact if it’s leaked. Only a few employees have access to this data. Examples could be company audit information, vulnerabilities, and data leaks if any.

How to Classify Data in Your Organization

To fulfill most compliance regulations, an organization should be able to identify and categorize data and protect it accordingly. Here are some considerations that should be contemplated before starting the data classification process.

Types of Data in the Organization

Depending on the industry, an organization must identify the types of data it collects. For example, financial companies handle credit card information such as card numbers, expiration dates, etc. The Healthcare industry handles patient information such as lab reports and other health information. Other types of information that a company might hold include customers’ personal details and their social security numbers.

Data Classification Policy

The organization should have a data classification policy that identifies the data it stores and defines the classification level of each type of data. For example, the general information of the company will be public, and its federal tax information will be restricted. Companies can have a simple policy since most compliance requirements don’t specify the levels of data classifications.

Data Ownership

In many organizations, there’s a data protection officer or a similar position that would determine the ownership of data in the company. While it’s not mandatory to assign an owner to each piece of data, doing so helps the organization with its data classification process.

Data Access

It’s important to know who can access which type of data. There are different levels of employees in an organization, and they typically have different access levels. For example, while a particular employee can view certain data, they may not be able to add, modify, or delete it.

Data Classification Best Practices

Here are some best practices that will help organizations with data classification.

Conducting a Data Risk Assessment

With a data risk assessment, a company can understand compliance requirements and determine confidentiality regulations. The data classification objectives should be discussed with all stakeholders including security, legal, and IT teams.

Creating a Data Inventory

A data inventory will help locate data using discovery tools. All data assets should be properly labeled according to how they are classified. This process can be automated to continuously monitor the data so that the data index is always up to date.

Establishing Security Controls

It’s important to establish policy-based controls at each classification level. Since not all data requires top-level security, organizations can save money by having strict security measures on only restricted data.

Maintenance of Controls

Once the security controls are deployed, they must be monitored regularly. Since data changes throughout its lifetime, an organization should know if the classification level of a particular data type has changed.

Leveraging Data Classification Software

Fortra DLP, especially when paired with Fortra's Data Classification, can help locate and identify sensitive data, label it according to your data classification policy, and determines how the data is handled. Offering automated content and context-based classification as well as manual user classification, all solutions are optimized for regulatory compliance.

Regulatory Compliance Requirements for Data Classification

For some organizations, data classification is required under laws and regulations, such as:

• SOX: The Sarbanes-Oxley Act (SOX) requires the classification and protection of financial data. It mandates a report signifying that the management is responsible for the protection of financial records.
• HIPAA: To get Health Insurance Portability and Accountability Act (HIPAA) certified, an organization needs to identify and protect sensitive health-related information.
• GDPR: The General Data Protection Regulation (GDPR) identifies and protects EU citizens’ personal information. It defines how an organization should handle the information of individuals who interact with them.
• PCI DSS: The Payment Card Industry Data Security Standard (PCI DSS) identifies and protects the details of credit and debit cards. This protects users from financial fraud and identity theft incidents.

Why Classify Data?

Data classification makes it easy to ascertain which data needs the most protection. Also, since data security is expensive, by classifying data, an organization can apply strict protection measures to only their restricted data, thereby lowering their security costs.

Data classification also helps Data Loss Prevention (DLP) tools like Network DLP and Endpoint DLP to do their job seamlessly. It’s easy to mark restricted information and confirm that it’s not mistakenly sent out in emails or office memos. It also ensures that confidential information isn’t stored on unsecured servers.

Conclusion

It’s important to know which data can be shared publicly and which data is the most sensitive and should be restricted. By using data classification, businesses are able to determine whether data should be considered:

• Public;
• Internal;
• Confidential;
• or Restricted.

By assigning the correct classification to data, businesses are better able to protect that data and to prevent sensitive information from being stolen and used in a manner that can cause harm to the company and to others. For more in-depth information about data classification, download our  Definitive Guide to Data Classification.