How do you classify sensitive data for cybersecurity risk assessment?

1 Define sensitive data

Sensitive data is any data that contains personal, confidential, or proprietary information that could cause harm or damage if compromised. Examples of sensitive data include customer records, financial transactions, health records, intellectual property, trade secrets, and employee data. The level of sensitivity may vary depending on the context, purpose, and legal requirements of the data.

2 Identify data sources and locations

To classify your sensitive data, you need to first identify where it is stored and how it is accessed. This includes both internal and external data sources, such as databases, servers, cloud platforms, applications, devices, networks, and third-party providers. You also need to map the data flows and interactions among these sources and locations, and document the data owners, custodians, and users.

3 Apply a classification scheme

A classification scheme is a set of criteria and labels that describe the sensitivity and security requirements of the data. There are different types of classification schemes, such as the ones based on the CIA triad (confidentiality, integrity, and availability), the data protection levels (DPLs), or the information classification levels (ICLs). The choice of the scheme depends on your organizational goals, policies, and standards. The scheme should be clear, consistent, and easy to apply and communicate.

4 Assign a classification level

Based on the classification scheme, you need to assign a classification level to each data element or dataset. This level determines the degree of protection and control that the data needs. For instance, a four-level scheme may include Public, Internal, Confidential, and Secret. Public data can be freely accessed and shared without any restrictions or impact. Internal data is intended for internal use only and could have some impact if disclosed to unauthorized parties. Confidential data contains sensitive information that could cause significant harm or damage if compromised, and requires strict access control and encryption. Finally, Secret data contains highly sensitive information that could cause severe harm or damage if compromised, and requires the highest level of security and protection.

5 Review and update the classification

Data classification is not a one-time activity, but a continuous process that requires regular review and update. You need to monitor the changes in the data lifecycle, such as creation, collection, processing, storage, transmission, use, and disposal. You also need to consider the changes in the business environment, such as new regulations, threats, or opportunities. You should update the classification level accordingly, and communicate it to the relevant stakeholders.

Data classification is a key component of data governance and cybersecurity risk assessment. It helps you identify and protect your sensitive data from cyberattacks, and comply with the legal and ethical obligations. By following these steps, you can classify your sensitive data effectively and efficiently.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?