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Data Classification Policy Template

On average, security teams spend over 76% of their time on data privacy-related tasks. 

With GDPR, CPRA, and other increasingly strict regulations being enforced across the globe, businesses need a solid plan for categorizing their data. At the core of this is implementing a data classification policy.

Fortunately, you don’t have to spend hours creating a policy from scratch. Whether you have a fully-staffed security team or rely on one team member to handle data privacy and security policies, starting with a template can save you loads of time.

Download Your Template

Download and adjust this template to help you establish the parameters your company will use when classifying data. 

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Data Classification Policy

In the next few years, the total amount of global data is expected to surpass 150 zettabytes. For comparison, in 2010 there were only two zettabytes of data captured worldwide. With all of this data floating around the web and company servers, data classification simplifies how you search, track, and filter data. Data classification is the process of categorizing your data by sensitivity, type, and value. A business’s data classification policy lays out that process of data categorization. Good data classification practices can simplify how you search, track, and filter data within your company.
Learn more about the ins and outs of what a data classification policy is, building one for your business, and how to implement it below.

Building Your Policy

Because data is stored, processed, and used in almost every aspect of a company—not just the security team—building a clear and concise policy is essential. All employees should be able to understand and use the policy effectively.
 
Here’s what your policy should include:
 

  1. Purpose
    Explain why data classification is performed and how it’s beneficial to the organization.

  2. Scope
    Discuss the types of data being categorized, determine who is responsible for appropriate data classification, security, and handling. This section should include not only company employees but vendors, partners, or other third parties who may have access to the data.

  3. Roles and Responsibilities
    Outline the roles and responsibilities affiliated with the data classification effort. For example, these roles may include data owners, data users, and data custodians. Each department will designate individuals or teams to carry out the responsibilities associated with the roles defined.

  4. Data Classification Procedure
    Walk through each data classification procedure and explain it step by step. This will include detailed descriptions of which role executes each step, how data is examined for sensitivity, and more.

  5. Data Classification Guideline
    Develop a table that contains each type of information asset your organization stores, specifies the impact or risk level associated with different security objectives, and defines the impact levels and classification to be assigned to each type of resource. This table can be used to determine the cumulative impact for a majority of data assets commonly used throughout the organization and among third parties.

  6. Impact Level Determination
    Create another table that will help one of the roles you have previously defined, data owners, assess the impact level for each piece of data according to the security objectives you want to achieve. Include what the effects would befall your organization if failing to attain any of the objectives.

  7. Handling requirements

    Some types of data may have particular handling requirements you’ll need to implement. You might choose to implement different security controls for an email containing restricted data than you would for a file on your file share containing restricted data.

    In these cases, your data classification policy should include a table listing different categories of data, their classification levels, and any specific handling requirements each category might require.


  8. Labeling Requirements
    Depending on the intent of your data classification policy and the specific needs of your organization, you may need to apply labels to specific data types or information assets. A common example of this would be emails containing sensitive information. A common approach to labeling these emails is to put the word “Confidential” or similar in the subject line of the email.

  9. Examples (Optional)

    Add examples of data types and classification levels. Some organizations include a separate table within their data classification policy which contains examples of data classified at each level.

    For example, if you have four data classification levels: Restricted, Confidential, Internal Use Only, and Public, you may elect to build out a table requiring all payroll data to be classified as Restricted by default. This is a good item to implement if you have a wide variety of data within your organization to eliminate any confusion among your employees regarding how data is classified.

Implementing Your Data Classification Policy

Every company will have its own security needs for the data they manage, process, and store. Now that you’ve tailored your data classification policy to your organization, you’ll need to build an implementation plan. There isn’t a one-size-fits-all approach to implementing but we’ve written up some steps below to get you started.
 
  1. Determine project objectives. Is this project company-wide or for a specific department or team?
  2. Figure out your approach to data labeling. Will you label each file individually or classify data at the file level, for example.
  3. Determine who will be involved in your project for implementing your data classification policy.
  4. Prepare your tool set. What tools may be necessary for your company’s data classification process. Do you need new software? Are your current tools up to the kind of workload your teams will need it for?
  5. Establish specific classification labels and create consistency in data classification policies. List specific elements like access restrictions, acceptable technologies for transporting data (such as authorized messaging systems or email providers), and determine data protection controls like encryption.
  6. Create a timeline for implementation of your policy. Do you need to have this implemented within six months? A year? Is there a plan to revisit the policy at a future time to determine success and any necessary changes?
  7. Train your personnel on your data classification policy. Before you begin applying security controls or data classification labels, your personnel should be made aware of any changes to their day-to-day work.
  8. Kickoff your data classification implementation project.
  9. Begin classifying data throughout the organization—including varying degrees of sensitivity—and assess who needs to have access to what information. In a Zero Trust world, gating access to information helps maintain data integrity and security.
  10. Enforce the classification policy. More security awareness throughout the organization brings security risks to the forefront of employees’ priorities.

Data Classification Policies in Use

Example of Data Type Handling and Labeling Requirements
Handling Controls Restricted Confidential Internal Use Public
Email (with and without attachments)
  • Encryption is required
  • Do not forward

 

  • Encryption is recommended
  • Do not forward
  • Encryption is recommended
  • Do not forward
  • No special requirements
Labeling
Subject line must include: “Restricted”
Subject line must include: “Confidential”
N/A - No labeling requirements
N/A - No labeling requirements

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