Data segregation is the process of separating certain sets of data from other data sets so that different access policies can be applied to those different data sets. The ultimate goal of doing so is only allowing the individuals who are authorized to view certain data set access to them.
There are many reasons why organizations may need to segregate their data, from regulatory requirements, systems that are shared between different entities in relationships like joint ventures, mergers, acquisitions and divestitures, or systems that are shared by many people within an organization that does not all have the same authorization to view all of the data. We cover some of the main reasons why organizations need to implement data segregation in a separate post.
Types of Data Segregation
- Physical Segregation – Separating and storing data on different physical systems or networks. While this may prevent someone from accessing the data if they don’t have physical access to the systems where it is stored, it also requires the expense of setting up different systems for the data sets that need to be segregated. Data storage regulations may require physical segregation, however, especially in the case where data is not allowed to leave a country’s borders or there are restrictions sending data to certain countries. By implementing physical separation, organizations can comply with export regulations of this nature.
- Logical Segregation – Separating and storing data in separate logical partitions or storage areas, even if those partitions or storage are on the same physical device. This can be much more cost effective than physical segregation and allows organizations much more flexibility in designing and implementing data access policies. Because all data is physically on the same system, changing data access policies or who can access specific data sets can be done by modifying the logical rules, instead of physically moving data, or changing who has physical access to the systems.
Why do organizations need to implement secure data segregation?
There are several reasons why data segregation is important:
- Data Protection and Security:Â Segregating data allows you to apply appropriate security measures based on the sensitivity of the information. By separating sensitive data from less critical data, you can implement stricter access controls, encryption, monitoring, and other security measures to protect sensitive information from unauthorized access, breaches, or misuse.
- Compliance with Regulations: Many industries and regions have specific regulations regarding data protection and privacy, such as the General Data Protection Regulation (GDPR) in the European Union or the Health Insurance Portability and Accountability Act (HIPAA) in the United States. Data segregation helps you comply with these regulations by ensuring that personal, sensitive, or regulated data is handled according to the required standards.
- Risk Mitigation:Â By segregating data, you can mitigate the potential impact of security incidents or data breaches. If an unauthorized user gains access to one category of data, segregating it from other types of data can help contain the breach and minimize the exposure of sensitive information.
- Data Management and Efficiency:Â Organizing data into separate categories or segments can improve data management and efficiency. It allows for easier identification, retrieval, and analysis of specific data sets, enabling better decision-making, reporting, and data governance.
- Business Continuity:Â Data segregation can support business continuity efforts. By categorizing data based on criticality or importance, you can prioritize backup, disaster recovery, and continuity plans accordingly. In the event of a system failure or data loss, you can focus resources on restoring and recovering the most vital data first.
Because of the potential impact unauthorized access can have on a business, it is very important that organizations implement robust data segregation measures to limit access to sensitive data. On shared systems, since data cannot be segregated physically, it must be segregated virtually, using a combination of data access policies and encryption to make it impossible for unauthorized access to the data.
Implementing data segregation at a lower level, such as the data access level, can make that segregation more robust and less likely to be compromised by reducing the systems or applications that have access to the data. Segregating on the data object level can also be less complex, and the less complexity there is in the system, the less chance there is of something going wrong.
How should organizations implement a data-centric approach to data segregation?
When designing and implementing effective logical data segregation measures it is important to focus on the specific data that needs to be protected, not the systems or networks where that data is stored or processed. This is what is meant by a taking a data-centric approach to security. Controlling access at the data level, using attributes of the data, the environment, and the user requesting access (known as Attribute Based Access Control, or ABAC  is one of the core principles of Zero Trust Architecture (ZTA), and is a more effective approach because a smaller number of attribute-based data access policies can be defined that cover all of the necessary scenarios, instead of writing separate policies for each combination of attributes.
Learn more about data segregation in our blog “Implement Data Segregation with Zero Trust.”
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