What is a Data Classification Matrix?

Anna Szentgyorgyi-Siklosi | 6 min read| Updated On - July 10, 2023

Data Classification Matrix

A Data Classification Matrix is a tool that is used to organize and classify different types of data according to their importance, sensitivity, and confidentiality. The matrix is a grid-like structure that categorizes data into different levels based on their risk level and assigns corresponding security controls to each level. Typically, data is classified into four categories: public, internal, confidential, and restricted. Each category has a specific set of access controls, authentication requirements, and authorization restrictions. The matrix helps organizations to manage and protect their sensitive data by applying appropriate security measures based on the data’s classification level.

How to Create a Data Classification Matrix

There are numerous data classification matrix templates that you can use, and you will need to choose one that precisely fulfils your requirements. The following is an example of a matrix that consists of four classification levels: public, internal, confidential, and restricted.

	Public	Internal	Confidential	Restricted
Risk Level	No risk	Low	Medium	High
Description	Data that is freely available and accessible to the general public. This type of data can include government publications, open access research papers, census data, and other freely available datasets.	Data that is generated and owned by an organization or its employees. This may include sales figures, customer data, financial records, and other sensitive information that is not intended for public consumption.	Data that is strictly protected and only accessible to authorized individuals. This may include PII, trade secrets, financial information, or any information that could cause harm if compromised.	Data that is highly sensitive and should only be accessed by authorized personnel on a need-to-know basis. It includes data that, if compromised, could cause significant harm to an organization or individuals.
Access Rights	No restrictions or access controls, available to anyone.	Limited access to certain individuals or groups within the organization.	Access only granted to those with a legitimate need to know, such as authorized employees or contractors.	Highly sensitive data with strict access controls, available only to a select few top-level employees or executives.
Impact	A breach of public data will not harm individuals or the organization.	The publication of this data may cause some inconvenience.	In the event that this information falls into the wrong hands, the consequences may result in losses that are not deemed crucial to the business.	The impact of this data being revealed to the public can be devastating to the company and possibly its customers.
Examples	Government publications and reports Census data Land records and property deeds Court records and judgments Press releases and news articles Company annual reports Whitepapers and research studies Social media posts and profiles that are set to public Weather and traffic data Publicly available financial statements of companies	Employee records Financial data Operational data Intellectual property Research and development HR-related data Marketing data Legal documents IT infrastructure and network information Administrative data	Financial data Medical records Legal documents Trade secrets Intellectual property Military information Government secrets Personal identifiable information Diplomatic cables Classified research data	Social Security Numbers (SSNs) Credit Card Information Passwords Classified Government Information Medical Records Criminal Records Financial Statements Trade Secrets Intellectual Property Personal Identifiable Information (PII) Confidential Legal Documents Proprietary Software Code
Storage Options	Can be stored on public servers or cloud storage systems that can be accessed by anyone with an internet connection.	Can be stored on internal servers or cloud storage systems that are accessible only to employees within the organization.	Should be stored on secure servers or cloud storage systems that are accessible only to authorized personnel with appropriate security clearances and credentials.	Should be stored on highly secure servers or cloud storage systems that are accessible only to a select few individuals with specific security clearances and strict access controls.
Additional Security Considerations	No security measures are required to access public data. However, it should be protected against unauthorized modification and deletion. For example, backups and logs should be maintained to provide data integrity and availability.	In addition to access controls, monitoring, logging, and encryption, should be implemented to protect internal data.	In addition to access controls, data loss prevention software and encryption should be implemented to protect confidential data from unauthorized use, storage, modification, and disclosure.	Restricted data is protected by additional layers of security, including multi-factor authentication, encryption, monitoring, and specialized access controls. Data should be stored on a server with high-level security and restricted to a small group of senior staff.
Audit Controls	No audit controls required.	It may be necessary to conduct some form of monitoring or review.	The task of monitoring and evaluating the system for misuse is assigned to data stewards. They must report any anomalous activities to their superiors based on the severity of the incident.	The duty of data stewards involves monitoring and evaluating the system for any possible instances of misuse or unauthorized entry. To address any issues promptly, a contingency plan must be in place.

Data Classification Matrix Best Practices

Talk with Experts: Before creating a data classification matrix, it’s important to discuss with in-house data experts or hire an agency to guide you to the correct framework for your data types.

Define your objectives: Defining a goal is crucial before creating a classification matrix. Each data type should be mapped to the correct class, reducing the risk to sensitive information in the event of a security breach.

Define the Scope: To effectively regulate data, it’s important to define the scope of the matrix. This ensures that only the data you want to regulate is classified.

Assign Responsibilities: Assigning ownership to data makes it easier to classify. Defining ownership becomes simpler once the scope of the matrix is established.

Assign Safety Grades: There are generally three to four safety grades based on the risk level of the data. Companies can add more safety grades as needed, but it’s best to keep the classification matrix simple.

Assign Safety Measures: Typically, three to four safety ratings are assigned based on the degree of risk. Businesses may have additional ratings based on their specific needs. Nevertheless, it is advisable to avoid overcomplicating the data classification system.

Keep Your Matrix Up-To-Date: Since data changes over time, its risk level can change as well. Therefore, its safety grades and measures should be regularly reviewed and updated.

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

Anna Szentgyorgyi-Siklosi

Anna is an experienced Customer Success Manager with a demonstrated history of working in the SaaS industry. She is currently working to ensure that Lepide customers achieve the highest level of customer service.