Data masking is a security and data privacy technique that obscures or anonymizes specific data elements within a database, application, or file. Its primary purpose is to protect sensitive information, such as personally identifiable information, protected health information, and financial data, from unauthorized access.

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Why is data security important in healthcare in particular? For one, healthcare organizations collect and store extremely sensitive patient information. In the wrong hands, it can be used for identity theft, fraud, and other malicious purposes. Its importance is only increasing, too: According to a report by the Ponemon Institute, 89% of healthcare organizations experienced cyberattacks — 43 on average — between 2021 and 2022.

Effective data security precautions

Healthcare organizations should implement comprehensive security measures, data privacy protocols, and risk management strategies to address these data security issues. This includes doing regular security risk assessments, implementing encryption and access controls, conducting regular training for employees, and ensuring compliance with data privacy regulations. By prioritizing data security, healthcare organizations can safeguard patient data and maintain trust with their patients.

Protecting patient privacy with data masking

Data masking is useful for resolving data security issues in healthcare. Essentially, data masking creates a duplicate of a database and replaces sensitive data with fictitious data that preserves the data’s structure and format. For instance, a financial institution may use data masking to safeguard its customers’ social security numbers or account numbers while enabling the testing and development of new applications with a production-like dataset. Credit card numbers, social security numbers, and names can all be masked to protect sensitive information without compromising the dataset’s integrity.

Data masking is crucial when third-party vendors or offshore teams handle sensitive data:

Companies can use it to ensure regulatory compliance without denying developers, analysts and testers the ability to work with real-time datasets. We all know by now that data privacy and security are necessary to protect sensitive information from unauthorized access, theft, or misuse. The consequences of failing to protect data can be severe; it could result easily in financial loss, legal liability, reputational damage, and loss of customer trust.

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How to prevent security breaches in healthcare

Data masking’s ability to reduce the risk of data breaches and theft by limiting access to sensitive information is arguably what makes it most useful.

Even if an attacker gains unauthorized access to a masked dataset, the information is useless without the means to de-identify the data. Now that you know why data security is important in healthcare, follow these five steps to start using it:

1. Identify sensitive data

Begin by identifying your most sensitive data. Scan all available resources and implement appropriate security measures to protect the data. When you know what data is on your servers and equipment, you can better protect it with cutting-edge techniques. This could mean using data masking or encryption to safeguard sensitive information.

2. Do your research

It’s essential to stay informed about the latest security threats and trends by regularly reviewing industry news and participating in relevant training and conferences. This can help you stay ahead of potential vulnerabilities and emerging threats. By proactively staying in the know, you will maximize your data protection.

3. Verify, don’t trust

Implement strong access controls and permissions for your data to ensure that only authorized users can view or modify it. This can involve setting up multifactor authentication and limiting user access based on job function or seniority. Because zero-trust architecture is necessary to fully protect all business systems and data, it’s now standard across all government systems.

4. Continuously audit your systems

Security and data privacy is not a one-and-done deal. It requires constant vigilance. Regularly audit your systems and data to identify and address any vulnerabilities or weaknesses in your security protocols. This includes conducting security assessments, penetration testing, and vulnerability scans to identify and remediate security risks.

5. Find the right solution

When implementing data masking, it’s important to carefully evaluate and select a solution that meets your organization’s needs, budget, and compliance requirements.

Consider factors such as ease of use, scalability, and data integrity when choosing a data masking tool. If the solution isn’t personalized to you, it could cause more problems than it resolves.

6. Apply masking when copying data to lower environments

Development and testing teams needing access to production-like data should leverage masking to ensure no sensitive data makes it into lower environments. This enables them to freely leverage that data without risking data breaches or compliance violations.

Data masking is an important technique that protects sensitive data in various applications. It uses fake data to conceal real data from unauthorized users. When facing modern cyber threats, data masking is foundational to protecting your business data.