Glossary

Data Classification Policy

Data classification plays an important role in ensuring that a given enterprise remains in compliance with applicable regulations. Having a data classification policy calls for thoroughly categorizing and storing all company data based on sensitivity level and the relative value of that data to your organization.

Creating a documented data classification policy is an often overlooked step for companies striving to remain in compliance, or who simply want to provide their clients with peace of mind. 

Many frameworks will require some level of data classification, so it’s a practice that every company should embrace. Data classification policies help companies prove their compliance with relevant regulations and maintain specific frameworks. It is essential on an organizational level.

Data Classification Policy

What is a Data Classification Policy?

A data classification policy is an extremely thorough plan that aims to categorize every piece of data found throughout the organization. The ultimate goal is to ensure proper handling of data throughout the entire organization, which in turn reduces operational risks. 

Once enacted, this policy will create a robust framework of rules, procedures, and processes for analyzing and categorizing data. Data deemed valuable and that could potentially harm the company is stored and handled differently from data that may only pose minor risks. Confidential and highly sensitive data is stored and accessed within the highest security possible, while less sensitive data is stored with lower security. 

You may be thinking: why not treat everything as high security? This would overconsume time and resources throughout the organization, along with giving access and revealing sensitive passwords and encryption keys to employees that may not have the company’s best interests in mind.

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The Main Types of Data Classification

Data categorization is the essence of a data classification policy. Each company can potentially have unique categories, such as public, controlled, restricted, and confidential. Conversely, a company might only need to categorize data as internal, external, and confidential. 

The purpose of data classification and categorization is to establish a set of written policies that detail how to handle, store, and transmit the information within each category. This means saving companies from needing to deeply analyze each bit of data, but instead, determine its category, and then the written policy will inform everything else. For example, having a confidential data classification will inform everyone in the organization about how to handle confidential information, regardless of when or where it was created.

It’s vital to keep in mind that keeping pace with compliance requirements and best practices is the ultimate goal of a data classification policy. If the regulations change, the policy will only need to be updated for your company to continue to operate without incurring fines.

Common Sections in the Data Classification Process

A complete data classification process will be incredibly thorough and be thousands of words long. However, to save time and impart the main goals, below are the primary sections that should be found in any data classification policy:

  • Purpose: The goal of such a policy is to create a unique framework that protects company data by detailing how data is created, analyzed, stored, processed, and transmitted. Creating the purpose paves the way for the following sections.
  • Scope: Are there any exceptions to the policy, or does it impact all data throughout the organization? The policy must clearly define its own scope. Traditionally, a data classification policy will cover all data found throughout the organization, but that’s not necessarily a requirement. 
  • Roles and responsibilities: Who is in charge of each step in the policy? This both includes crafting the policy and implementing it once it’s been created. Additionally, it must be clearly spelled out who will be responsible for analyzing data for risks, keeping controls up-dated, and ensuring that all classified information meets any relevant requirements. 
  • Categories of data classification: As discussed in the previous section, every company needs to determine its major types of classification, such as public, internal, and confidential

Why Have a Data Classification Policy?

There are plenty of benefits that make creating such a policy well worth the time. A few notable benefits are:

  • Establishes a unique framework for your company that contains all of the rules and procedures that any employee might need to properly evaluate and store data.
  • Creates an effective system that maintains data integrity along with staying in compliance with relevant regulations.
  • Unify all data throughout the organization by applying the same rules to each of them.
  • Helps IT understand which security controls require additional investment

A policy for data classification should be considered a requirement for any organization that must maintain compliance with a regulatory body.

Referring  to Security Standards and Laws in Data Classification

Many standards and regulations base their requirements on varying data sensitivity levels. For example, although the GDPR, ISO 27001, PCI DSS, HIPAA, and SOX all have completely different purposes in the realm of information security, a data classification process is an inherent requirement for compliance in all of them. 

A data classification policy ensures you can accurately identify and implement controls on various data types. 

Following is a list of data requirements in several well-known data regulations and standards.

GDPR Data Classification Requirements:

  • Definition of Personal Data:
    • Refers to information associated with an identified or identifiable natural person
    • Examples encompass phone numbers, physical addresses, driver’s license details, social security numbers, credit card information, IP addresses, bank account particulars, location data, utility records, work performance, and biometric data
  • Data Protection Impact Assessments (DPIAs):
    • DPIAs are critical in categorizing Personally Identifiable Information (PII) data
    • Involves analyzing workflows for collecting, storing, and deleting personal data
    • Evaluate the value or confidentiality of information and potential risks in a security breach

NIST 800-53 Data Classification Requirements:

The NIST 800-53 system classifies data into three primary types: public, sensitive, and confidential.

  • Public data: Openly accessible
  • Sensitive data: Requires additional security measures due to its significance
  • Confidential data classification: Demands the utmost protection due to the substantial risk if exposed or misused

Risk Evaluation of Data Classification Categories

  • Conducting risk assessments to comprehend associated risks with diverse data categorization types.
  • Assurance of appropriate security measures aligned with data classification.

ISO 27001 Data Classification Requirements:

  • Information Security Management System (ISMS):
    • Adoption of the ISO 27001 ISMS for data classification
    • Establishment of a framework for categorizing sensitive information
  • Data Categorization:
    • According to ISO 27001, the category of data includes intellectual property, customer data, financial records, employee information, personal data, and other confidential or sensitive data
  • Security Measures:
    • Selection of suitable security measures per the value and sensitivity of information
    • Ensuring compliance with local and international regulations related to protecting personal data and privacy rights

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Centraleyes for Free

See for yourself how the Centraleyes platform exceeds anything an old GRC
system does and eliminates the need for manual processes and spreadsheets
to give you immediate value and run a full risk assessment in less than 30 days

Want to talk to Centraleyes about Data Classification Policy?

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