Best practices for securing sensitive data

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Sensitive data broadly defines any business-critical content, including but not limited to proprietary information, employee and customer personal data, and payroll information. By securing all forms of sensitive data within your organisation, you can ensure a good business reputation is retained, and compliance with data security mandates are met. Here are six best practices to help you locate sensitive data within your data stores, find vulnerabilities and risks, and enable the secure storage and use of that data.

6 best practices for securing sensitive data


Define sensitive data and use eDiscovery to locate it

Create a data security framework within your organisation that delineates what encompasses sensitive data. Ideally, it should include all types of PII, ePHI, financial information, payment card data, etc. Use data discovery software to help locate and create an inventory of the various types of sensitive data stored across data repositories, including databases, file servers, and cloud applications.


Classify sensitive data based on its vulnerability

Understanding the level of sensitivity of the data stored helps to add the correct classification tag to it, which in turn is vital to enforce the right levels of data security standards to it. This risk-based approach to data security assesses the various components of a file, including the volume of sensitive data stored, permission levels, data type, and ownership details, before assigning a classification label to it. Use a combination of both manual and automated classification functionalities for better accuracy and efficiency.


Enable strict data access control measures

Control and limit employees' access to files containing sensitive information to the bare minimum that is required to carry out their daily operations. This practice is referred to as the principle of least privilege. It helps keep data secure, because overexposed files with unnecessary privileges act as unguarded thresholds through which malicious insiders could perpetrate sensitive data theft and sabotage.


Protect sensitive data in every state

Implement technical control based on the risk profile of the data that needs to be secured in all its states—in use, at rest, and in motion. These measures should include data encryption and anonymisation strategies, vulnerability management across servers and applications, ensuring file integrity, and others. A dedicated data leak prevention tool helps limit data movement and access, thereby preventing sensitive data exposure.


Curtail unnecessary storage of sensitive data

Find sensitive data stored within your organisation without legitimate business reasons, and process it appropriately. The increasing cost of secure storage and stringent compliance mandates calls for a comprehensive data life cycle management solution to help archive or purge unneeded sensitive information.


Map out an acceptable data security policy

A comprehensive data security policy should include data use and processing guidelines, data privacy requirements, breach notification templates, remote access plans, regular backup schedules, and more. It is vital to revise them periodically and follow security best practices stringently to stay ahead of evolving threats to sensitive data.

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