Protecting your sensitive data while preserving its value

As the amount of data collected and stored by organisations continues to increase, so does the threat of data breaches and cyberattacks.

With cybersecurity horror stories now dominating the headlines, businesses must be more vigilant than ever about securing their sensitive data.

Data is a highly valuable currency for businesses and cybercriminals alike, and protecting it is a non-negotiable.

So what happens when an organisation needs to leverage its data for testing, application development, analytics, or training? Without risking a data or privacy breach, or losing value from the data?

Many organisations are still making compromises. They either expose private information internally or to a third party – which not only creates a vulnerability for cybercriminals, but also breaches privacy regulations, and compliance measures under SOC 2 and ISO 27001. Or they try to handcraft or de-identify the data themselves, removing its fidelity and utility.

Data masking can eliminate the need to take such unnecessary risks.

Data masking involves altering or obfuscating sensitive data so it becomes unidentifiable to unauthorised users, but, when implemented correctly, still maintains its functional integrity.

It does this by replacing the original data with realistic fictional data that can retain the format and structure of the original data, while rendering it useless to those without authorised access. This gives organisations the freedom to use this synthetic data without putting private customer information at risk.

How data masking works

What information can data masking protect?

• Personally Identifiable Information (PII)

PII can include a person’s name, date of birth, address, telephone number, and more. PII is highly valuable to cybercriminals as it can be used for identity theft and other fraudulent activities. Masking this sensitive data can help organisations protect their customers.

• Protected Health Information (PHI)

PHI is any individually identifiable health information. This can include medical records, lab results, insurance information, and more. Data masking can help healthcare organisations ensure the confidentiality of their patients’ PHI.

• Payment Card Information (PCI)

Payment card information, which includes credit card numbers, expiration dates, and security codes, is a prime target for cybercriminals. By masking this data, companies can secure their customers’ financial information and help prevent fraud.

• HR Information

HR information includes employee data such as names, salaries, and performance reviews. Data masking can help organisations protect their employees’ privacy and prevent any potential misuse of this sensitive information.

• Any other sensitive data

This can include information such as trade secrets, financial data, or confidential product information. Data masking can protect all of these types of data to help prevent potential financial loss, reputational damage, and legal repercussions.

Why should an organisation mask data?

There are several reasons why organisations should consider using data masking to protect their sensitive data:

• Achieve regulatory compliance
  Under regulations such as the General Data Protection Regulation (GDPR), organisations are legally obligated to protect their customers’ data. By ensuring the security and privacy of sensitive data, data masking helps organisations achieve regulatory compliance.
  

• Attain ISO certification
  Data masking is now mandated as part of the ISO 27001 international standard for information security management. This requirement shows that data masking is more than a nice-to-have data protection strategy.
  

• Accelerate development and testing
  One of the biggest challenges for development and testing teams is accessing high-quality data that is both realistic and secure. Data masking solves this problem by providing useful anonymised data that doesn’t compromise security.
  

• Enable data sharing
  Data masking allows for safe and secure data sharing between third parties and wider internal teams, as the masked data cannot be linked back to the original data owner.
  

• AI development
  With data masking, businesses don’t have to share real customer data with large language models (LLMs) for training and model development. Masking data before uploading it into an LLM allows organisations to train their AI models without compromising customer data privacy.
  
  As organisations rely more on data to drive their operations, securing and protecting that data is now a top priority. Data masking offers a practical and effective solution to ensure the security of sensitive data while supporting organisational needs.
  
  It is a crucial tool many organisations should think about adopting to combat data breaches and protect individuals’ privacy.

An example of data masking in action

Data privacy and security is critical for all types of organisations, especially those that handle sensitive personal information.

This case study examines how a leading global hotel chain uses data masking as part of its data protection strategy, not only to maintain the trust of its guests, but also comply with data privacy regulations.

Discover how your organisation can safeguard data and maintain its utility

Visit https://datamasque.com/software/ today.