What is a Data Classification Policy and How Does It Works?

What is a Data Classification Policy?

A data classification policy is a set of guidelines and procedures that an organization establishes to classify and categorize its data according to the degree of its sensitivity or importance. The aim is to protect critical organizational information by identifying and controlling access to it, monitoring its usage, and ensuring its integrity and confidentiality. The policy outlines the different categories of data, such as public, internal, confidential, or restricted (highly confidential), and defines the appropriate security measures, access controls, storage, and disposal methods for each category. It also identifies the roles and responsibilities of employees in managing and safeguarding data according to the level of access granted to them. The policy plays a critical role in preventing data breaches and protecting an organization’s reputation, confidential data, and intellectual property.

How Do Data Classification Policies Work?

A data classification policy delineates several aspects within an organization. It involves the comprehensive assessment of all types of data owned by the organization, followed by the categorization of data based on storage requirements and permission rights. This categorization may include designations such as sensitive, public, confidential, or personal. Additionally, the policy should account for any particular data classification levels or categories mandated by industry regulations or standards. The implementation of data classification policies empowers organizations to enforce the requisite level of security measures for their data, thereby mitigating the overall risk to the company.

What Should Data Classification Policies Contain?

Data classification policies play a crucial role in protecting sensitive information and minimizing risk within an organization. To be effective, these policies should contain several key elements:’

1. Purpose and Scope:

• Purpose: Clearly state the objective of the policy, which is typically to categorize data based on its sensitivity and establish appropriate handling procedures.
• Scope: Define the data covered by the policy, including physical (paper documents) and digital data (electronic files, emails, databases). Specify any exemptions, if applicable.’

2. Data Classification Levels:

• Establish different classification levels based on the data’s sensitivity and potential harm if compromised. Common categories include:

  1. Confidential: Highly sensitive data, like financial records, personal information, or trade secrets.
  2. Internal: Sensitive but internally relevant data, like business plans or company strategies.
  3. Public: Non-sensitive information publicly available or suitable for release.
• Clearly define the criteria for assigning each level to different data types.

3. Handling Procedures:

• For each classification level, outline specific instructions for:

  1. Access: Determine who can access the data and under what circumstances.
  2. Storage: Specify appropriate storage methods (encrypted drives, secure cloud platforms) based on sensitivity.
  3. Transmission: Define secure methods for sharing data internally and externally (email encryption, password-protected files).
  4. Disposal: Establish procedures for securely deleting or disposing of no longer needed data.

4. Training and Awareness:

• Emphasize the importance of data classification for all employees through training programs and awareness campaigns.
• Provide clear guidelines on how to identify and classify data accurately.

5. Enforcement and Audit:

• Clearly outline consequences for non-compliance with the policy.
• Establish mechanisms for regular audits to monitor adherence and identify any potential vulnerabilities.

Additional Considerations:

• Compliance with Regulations: Ensure the policy aligns with relevant data privacy and security regulations (e.g., GDPR, HIPAA).
• Regular Review and Updates: Regularly review and update the policy to reflect changes in technology, legal requirements, and organizational practices.

By incorporating these elements and tailoring them to your specific needs, you can create a comprehensive data classification policy that effectively protects your valuable information and mitigates data-related risks.

How to Create/Implement a Data Classification Policy

Below are the steps to create a data classification policy:

1. Identify the types of data you collect and process

Start by defining the types of data you collect, such as personal data, financial data, confidential information, and sensitive business data.

2. Categorize the different levels of sensitivity

Once you have identified the types of data, categorize them based on the level of sensitivity. You can use a classification scheme, such as public, internal, confidential, or restricted, or define your own classification based on your business needs.

3. Define the access levels

Once you have classified the data, define the access levels for each category. Access levels should be restricted to only authorized personnel, and the policies and procedures should be clearly communicated to ensure compliance.

4. Define the storage and disposal procedures

Determine how the different types of data should be stored and disposed of. Define the procedures for storing and backing up the data to protect against loss and theft. Additionally, consider how the data should be destroyed when it is no longer needed.

5. Include contingency plans

Contingency plans should be developed in case of an emergency such as a breach or a system failure. Ensure that a clear plan is in place for addressing any incidents and that employees are trained to follow the procedures.

6. Assign roles and responsibilities

Clearly define the roles and responsibilities of various stakeholders such as data owners, data custodians, and data processors to ensure that everyone understands their responsibilities.

7. Regularly review and update the policy

The data classification policy should be regularly reviewed and updated to ensure it is meeting business needs. Companies must also make note of any changes to the regulatory requirements.

Data Classification Policy Best Practices

Here are some best practices for crafting and implementing an effective data classification policy:

Keep it Simple: Avoid overcomplicating your policy with too many classification levels or complex criteria. Aim for a clear and concise framework with 3-4 readily understandable levels (e.g., Confidential, Internal, Public) to ensure consistent application and user adoption.

Align with Regulations: Identify the data privacy and security regulations applicable to your organization (e.g., GDPR, HIPAA) and ensure your policy meets their requirements. This helps avoid legal complexities and compliance issues.

Start with a Data Inventory: Conduct a thorough data inventory to identify and map all data assets within your organization. This helps understand the types of data you hold, their locations, and potential risks associated with them.

Risk-Based Approach: Instead of a one-size-fits-all approach, assign classification levels based on the potential harm caused by a data breach. Prioritize highly sensitive data (e.g., financial records) and implement stricter controls for their protection.

Leverage Automated Tools: Consider using data discovery and classification tools to automate the process of identifying and classifying large data volumes. This saves time, resources, and improves the accuracy of classification.

Empower Data Owners: Define data ownership within your organization and entrust responsible individuals with classifying their data assets. This promotes accountability and ensures data classification accuracy.

Train and Educate: Regularly train all employees on the importance of data classification, policy provisions, and identification techniques. Foster a culture of data security and encourage employees to report potential classification inconsistencies.

Maintain and Update: Data classification is not a one-time activity. Regularly review and update your policy to reflect changes in regulations, business processes, and new data types. Conduct periodic audits to assess compliance and identify areas for improvement.

Communicate Effectively: Ensure clear and consistent communication of the data classification policy to all stakeholders. Make the policy readily accessible and provide channels for employees to seek clarification or raise concerns.

Continuously Improve: View data classification as an ongoing process, not a static document. Actively seek feedback from employees, IT teams, and legal counsel to identify opportunities for improvement and adapt the policy to evolving needs.

How Lepide Helps with Data Classification

The Lepide Data Security Platform can make data classification easier and more efficient, ensuring that sensitive data is properly protected, and compliance requirements are met.

Our solution allows you to identify sensitive data, as well as monitor access and user activities related to it, allowing for the implementation of appropriate access controls and security measures. It can even classify data at the point of creation/modification.

Our solution will automatically scan your repositories, whether on-premise or cloud-based, to identify sensitive data like personally identifiable information (PII), financial data, and intellectual property. Once identified, it will tag the data with appropriate labels based on predefined rules. You can also classify data in accordance with the relevant compliance regulations, such as HIPAA, SOX, PCI, GDPR, CCPA and more.

If you’d like to see how the Lepide Data Security Platform can help you classify your sensitive data, schedule a demo with one of our engineers.