Masking data protects the privacy of individuals and organizations who are the subject of research. By masking the data, researchers cannot identify any specific individual or organization. This prevents the data from being used for unintended purposes, such as marketing or discrimination. There are many different types of data masking software available. It can be challenging to know which one is right for your organization. Keep reading to learn about the various data masking examples of software and how to choose the best one for your needs.
Identify the Masking Criteria
Masking data is a process of obscuring individual values in a data set to protect the data owners’ privacy and comply with data protection regulations. There are a variety of criteria that can be used to determine how to mask data, including:
- The type of data being masked
- The sensitivity of the data
- The jurisdiction in which the data is being processed
When masking data, it’s essential to ensure that it remains anonymous and that it’s impossible to reconstruct the original data set from the masked data. There are a variety of techniques that can be used to mask data, including:
Randomization: This technique randomly selects values from a data set to replace the original values.
Substitution: This technique involves replacing the original values with substitute values.
Encryption: This technique involves encrypting the original values so that they cannot be read or understood.
When choosing data masking software, there are several factors to consider. One of the most important is the software’s level of security. You want to make sure that the software uses robust encryption algorithms and is up to date with the latest security protocols.
Masking Data Software
Masking data obscures specific information in a dataset before it is shared with third-party individuals or organizations. This is done to protect the privacy of the individuals included in the data and ensure that the data cannot be used to identify those individuals. Several different types of data masking software are available, each with its own set of features and capabilities. Some of the most common types of data software include:
Data obfuscation software: This type of software is used to scramble or alter the structure of sensitive data so that it cannot be easily understood or interpreted. Data obfuscation can hide individual values within a dataset or completely obscure all identifiable information.
Data redaction software: This type of software is used to selectively remove certain pieces of information from a dataset before sharing it with others. While this approach can be time-consuming, it can effectively protect highly sensitive data sets.
Anonymization tools: These tools are designed specifically for anonymizing large datasets by removing all identifying information (e.g., names, addresses, social security numbers). Anonymization can effectively protect individual privacy while still allowing for research and analysis of large datasets.
Data discovery and protection (DDP) software: Data discovery and protection (DDP) software is a software-only solution installed on-premises. It’s also used to ensure compliance with data privacy regulations such as GDPR.
Data loss prevention (DLP) software: Data loss prevention (DLP) software is a software-only solution installed on-premises. DLP software is used to protect data from alteration or theft.
Dynamic masking software: Dynamic masking software is designed to protect data in motion. It’s a software-only solution installed on-premises, protecting data from unauthorized access, alteration, or theft.
Cloud-based masking software: Cloud-based masking software is a software-as-a-service (SaaS) solution hosted in the cloud.
Static masking software: Static masking software is designed to protect data at rest. It’s a software-only solution that is installed on-premises.
When choosing which data masking software is suitable for your needs, it’s essential to consider your budget and specific requirements. Most commercial products offer a variety of features and options that can accommodate a range of conditions and budgets. However, if you need something more specialized or custom-built, many open source options are available that can be tailored specifically for your needs.