Data classification

What is data classification?

In data classification, data is categorized based on various parameters, such as sensitivity and vulnerability. It involves systematically labeling or tagging data so that organizations can protect their critical data with appropriate levels of security.

In today's compliance-driven landscape, the GDPR, HIPAA, and other regulatory bodies demand nothing less than a fortress around sensitive personal data. This can be done effectively only if this data is identified and classified appropriately.

Importance of data classification

Data classification plays a pivotal role in cybersecurity, helping organizations to:

  • Implement security measures based on the sensitivity of data.
  • Assess risks associated with sensitive data and mitigate them.
  • Meet multiple legal regulations and compliance requirements.
  • Manage data life cycles from creation to deletion.
  • Respond appropriately to security breaches.

Data classification types

Data classification methods in organizations include both automated and manual approaches, each offering distinct methodologies for categorizing and managing data. Commonly used methods of data classification include:

  • Content-based: An automated approach where the contents of files are reviewed and inspected to identify and classify information.
  • Context-based: The metadata of the file, such as the application, location, and creator, is taken into account and suitable tags are automatically applied.
  • User-based: This is a manual classification method that relies entirely on the user to classify data.

Data classification levels

While classification categories for data vary based on the organization's needs, the GDPR's data classification standard uses four levels of data classification:

  • Public: Data that is freely disclosed to the public and does not have any access controls in place.
  • Internal: Data with minimal security restrictions in place, intended for use within the organization, and whose disclosure presents a minimal impact to business.
  • Confidential: Files with high sensitivity and restrictions, intended for use within the organization, and whose disclosure presents a negative impact to business.
  • Restricted: Files that have the highest sensitivity and stringent access controls, whose disclosure could result in legal penalties.

Data classification examples

Classification level Example Data type
Public Webpages, blog posts, and company contact information Low sensitivity
Internal Company policy information, internal documents, and correspondence Medium sensitivity
Confidential Product pricing, marketing strategies, and revenue numbers High sensitivity
Restricted Personally identifiable information (PII), credit card numbers, and health information Highest sensitivity

Develop a data classification policy

To develop a data classification policy, follow these key steps:

  1. Identify data owners: Assign responsibility for data classification to individuals or teams within the organization.
  2. Define criteria: Establish clear criteria for classifying data, taking into account sensitivity, legal requirements, and business impact.
  3. Label and mark data: Develop a simple labeling system to mark classified data and ensure that employees understand and distinguish each level.
  4. Manage access controls: Implement access controls and authentication mechanisms to restrict data access according to its classification.

How can DataSecurity Plus help classify your data?

DataSecurity Plus offers a data classification tool that can identify files containing restricted data, assess how much threat they pose to the organization, and list users who own high-risk files. The data discovery and classification tool scans files to check for personally identifiable information, payment card information, protected health information, and more and allows you to classify files to enforce appropriate security and access measures for them.

The data classification tool also includes the following features:

  • Classify files by creating profiles for different file types based on the number of occurrences and risk scores based on data laws.
  • Anticipate potential data risks by analyzing files with highly sensitive data.
  • Configure alerts to track files that violate data protection laws like the GDPR, PCI DSS, and more.
  • Prioritize the security of payment card information with the card data discovery tool.
  • Identify users with high risk scores or the highest number of data violations and notifying them to address the risk immediately.

Try DataSecurity Plus' data discovery functions with a free, fully-functional, 30-day trial.

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