What Is Data Classification?

Definition

Data classification is a method for defining and categorizing files and other critical business information. It’s mainly used in large organizations that must use data classification to build security systems that follow strict compliance guidelines, but it can be used in small environments as well. The most important use of data classification is understanding the sensitivity of your stored information so that you can build the right cybersecurity tools, access controls, and monitoring around it.

Types of Data Classification

Any stored data can be classified into categories. To classify your data, you must ask several questions as you discover and review it. Use the following sample questions as you review each section of your data:

  • What information do you store for customers, employees, and vendors?
  • What types of data does the organization create when generating a new record?
  • How sensitive is the data using a numeric scale (e.g., 1-10 with 1 being the most sensitive)?
  • Who must access this data to continue productive operations?

Using these questions, you can loosely define categories for your data, including:

  • High sensitivity: This data must be secured and monitored to protect it from threat actors. It often falls under compliance regulations as information that requires strict access controls that also minimize the number of users who can access the data.
  • Medium sensitivity: Files and data that cannot be disclosed to the public, but a data breach would not pose a significant risk could be considered medium risk. It requires access controls like high-sensitivity data, but a wider range of users can access it.
  • Low sensitivity: This data is typically public information that doesn't require much security to protect it from a data breach.

Data Classification Levels

As you ask these questions, you can better classify your data. Data classification typically can be broken into four categories:

Public Data

This data is available to the public either locally or over the internet. Public data requires little security, and its disclosure would not result in a compliance violation.

Internal-Only Data

Memos, intellectual property, and email messages are a few examples of data that should be restricted to internal employees.

Confidential Data

The difference between internal-only data and confidential data is that confidential data requires clearance to access it. You can assign clearance to specific employees or authorized third-party vendors.

Restricted Data

Restricted data usually refers to government information that only authorized individuals can access. Disclosure of restricted data may result in irrefutable damage to corporate revenue and reputation.

Data Classification Process

When you decide that it’s time to classify data to meet compliance standards, the first step is to implement procedures to assist with data location, classification, and determining the proper cybersecurity to protect it. The execution of each procedure depends on your organization's compliance standards and the infrastructure that best secures data. The general data classification steps are:

  • Perform a risk assessment: A risk assessment determines the sensitivity of data and identifies how an attacker could breach network defenses.
  • Develop classification policies and standards: If you generate additional data in the future, a classification policy enables streamlining of a repeatable process, making it easier for staff members while minimizing mistakes in the process.
  • Categorize data: With a risk assessment and policies in place, categorize your data based on its sensitivity, who should be able to access it, and any compliance penalties should it be disclosed publicly.
  • Find the storage location of your data: Before you can deploy the right cybersecurity defenses, you need to know where data is stored. Identifying data storage locations points to the type of cybersecurity necessary to protect data.
  • Identify and classify your data: With data identified, you can now classify it. Third-party software helps you with this step to make it easier to classify data and track it.
  • Deploy controls: The controls you put in place should require authentication and authorization access requests from every user and resource that needs access to data. Access to data should be on a “need to know” basis, meaning users should only receive access if they need to see data to perform a job function.
  • Monitor access and data: Monitoring data is a requirement for compliance and the privacy of your data. Without monitoring, an attacker could have months to exfiltrate data from the network. The proper monitoring controls detect anomalies and reduce the time necessary to detect, mitigate, and eradicate a threat from the network.

Data Classification Examples

One of the most challenging steps in classifying data is understanding the risks. Compliance standards oversee most private sensitive data, but organizations adhere to the compliance regulations applicable to the different data stored in files and databases.

Here are some examples of data sensitivity that could be categorized as high, medium, and low.

  • High sensitivity: Suppose that your company collects credit card numbers as a payment method from customers buying products. This data should have strict authorization controls, auditing to detect access requests, and encryption applied data is stored and transmitted. A data breach would likely cause harm to both the customer and the organization, so it should be classified as highly sensitive with strict cybersecurity controls.
  • Medium sensitivity: For every third-party vendor, you have a contract with signatures executing an agreement. This data would not harm customers, but it still is sensitive information describing business details. These files could be considered medium sensitive.
  • Low sensitivity: Data for public consumption could be considered low sensitivity. For example, marketing material published on your site would not need strict controls since it’s publicly available and created for a general audience.

Importance of Data Classification

A data sensitivity level dictates how you're going to process and protect it. Even if you know data is important, you must assess the risks associated with it. The data classification process helps you discover potential threats and deploy cybersecurity solutions most beneficial for your business.

By assigning sensitivity levels and categorizing data, you understand the access rules surrounding critical data. You can better monitor data for potential data breaches, and most importantly, remain compliant. Compliance guidelines help you determine the proper cybersecurity controls, but you need to perform a risk assessment and classify data first. In many cases, organizations require a third party to help with data classification so that cybersecurity deployment can be more efficiently executed.