November 20, 2020
The key to successful data lifecycle management and security starts with a few essential activities — one of them being data classification. Data classification is the process of categorizing data based on their shared characteristics, like level of sensitivity or requirements for confidentiality, integrity and availability. The purpose of classifying data is to make protecting and using data easier and more efficient. However, the entire process of data classification will not render efficient results if an organization’s security team doesn’t have a formalized data classification policy.
What is a data classification policy?
A data classification policy ensures that a company’s collected sensitive information is safeguarded and handled appropriately to mitigate risks or threats to the organization. Security team leaders create data classification policies so that their team, and the organization as a whole, all have the same understanding when it comes to objectives, workflows, schemas and data owners.
Teams that have a clear understanding of roles, tasks and procedures can work more efficiently and accurately. When it comes to sensitive data and the risks associated with mishandling that information, businesses do not want to leave room for error. That is why it’s paramount for security team leads to create data classification policies, so that every employee in an organization can work together when it comes to protecting sensitive data.
How do data classification policies work?
A data classification policy is your organization’s framework that maps out roles, tasks and standard procedures. No two data classification policies will look exactly alike because they are developed for an organization’s unique workflows and needs. A few of the considerations that are factored into the development of a data classification policy include types of data, data ownership rights, storage and permission rights, and state, industry and federal laws and regulations.
Types of data to classify
A starting point for developing a data classification policy is assessing the types of data that your organization needs to classify. Data that falls into the “sensitive” category needs to be classified, as that piece of information could present risk for the organization depending on its level of sensitivity. Some examples of sensitive data include personally identifiable information (PII), protected health information (PHI), payment card industry data security standard (PCI-DSS), and biometric data.
Data classification labels
The types of data classification levels that an organization would like to use is completely dependent on their own workflows, types of data collected, and the laws and regulations that apply to them. In general, these are four classification levels that are commonly used:
- Public: Any type of data that is not personal or sensitive and is accessible by anyone.
- Internal: Data not intended for public disclosure but has low security requirements.
- Confidential: Data that could create moderate risk if disclosed to an unauthorized user.
- Restricted: The highest level of sensitive data that could put an organization at severe risk if disclosed to an unauthorized user.
How to classify data using security objectives
When classifying data, there are three primary objectives that should be considered.
- Confidentiality: Sensitive data should only be accessed by authorized users.
- Integrity: Sensitive data should be protected against improper modification or destruction.
- Availability: Sensitive data should be readily accessible to authorized users.
What information should a data classification policy include?
Each organization’s data classification policy will vary, but a good start to any policy will include the following eight areas of information.
- Purpose: Each data classification policy should begin with why data classification is being done at your organization and the benefits that it will bring.
- Scope: Here, you should define the types of data that need to be classified and who these procedures apply towards (employees, third-party vendors, etc.). It is good to be thorough and specify that the policy applies to any form of data, whether it’s on physical paper or in digital format.
- Roles and responsibilities: Designate which individuals are responsible for which tasks when it comes to your organization’s data classification efforts.
- Data classification procedure: Describe all data classification procedures step-by-step, detailing who is responsible for performing each step, how the data will be assessed for sensitivity, troubleshooting, and more.
- Impact level determination: Provide explanations for what makes a piece data have a low, moderate or high impact level when it comes to confidentiality, integrity and availability.
- Data classification guideline: Create a chart for each type of data asset that your company stores. In this chart, you should include a brief description of the data asset type, the impact level for each of the three main security objectives (confidentiality, integrity and availability), and the data classification label.
- Glossary: Provide definitions for the terminology used in the data classification policy so that the policy is easily understood by anyone in the organization.
Which businesses need data classification policies and why?
Many businesses collect sensitive data without even realizing that it exists in their networks. (This is where sensitive data discovery plays an integral role in data lifecycle management.) Most businesses will generally benefit from data classification policies, and organizations that collect large amounts of sensitive data are highly recommended to.
A few industries that typically manage large amounts of sensitive data and are highly regulated include businesses in the financial, healthcare, higher education, retail, manufacturing and the public sector. Since organizations that fall under these fields process a lot of sensitive data and have specific compliance laws and regulations they must adhere to, data classification is of utmost importance.
Benefits of data classification policies
Businesses have a lot to gain from proper data classification. Below are a few core benefits that have significant influence on an organization’s operations.
Improved data security
When a company has a complete view of their data assets and its availability, location, integrity and security measures, then they are able to effectively and efficiently protect sensitive data. This is especially important for businesses that obtain sensitive information, as unauthorized disclosure of sensitive data can result in financial and reputational damage.
Alongside financial and reputational risk is regulatory risk. Regulations like GDPR, CCPA, and HIPAA apply to most, if not all, organizations. Certain organizations may be subject to industry-specific regulations as well, like the GLBA for financial institutions.
Optimized security budgets
Depending on its level of sensitivity, the data that lives within your organization’s networks will have different security requirements. Once you have a clear view of exactly how much sensitive data your organization is storing, you may find that you have been overspending (or underspending) on the amount of specialized secure storage your company purchases. Data classification can help optimize those designated security funds.
Best practices for developing an effective data classification policy
Considering how important data classification policies are for businesses, it’s critical to keep in mind the factors that make your policy easy to understand and easy to implement by all in your organization. Follow these tips to ensure that everyone in your organization can easily follow your data classification policy.
Use clear criteria
Make sure that your company’s data classification policy uses criteria that is straightforward. Although a data classification policy should be generic enough to apply to different sets of data and unique circumstances, it’s important to be specific when possible to avoid confusion.
Use simple language
Your data classification policy should be easily understood by all members of your organization. That is why it’s important to include a glossary for specific data security terminology that may not be understood by all. In addition, organizations should ensure that the entirety of their policy content is written with simple, clear and concise language that is not jargon-heavy.
Customize it to your organization
Referencing other data classification policies is great for getting a sense of what needs to be included in your organization’s own data classification policy. However, it is crucial to tailor your policy to your company’s workflows, rules, and any applicable compliance laws and regulations.