What are the most effective data masking and anonymization tools for sensitive data?

1 Why mask and anonymize data?

Data masking and anonymization are not only good practices for data security and privacy, but also legal requirements in many cases. For example, if you need to comply with regulations such as the General Data Protection Regulation (GDPR) or the Health Insurance Portability and Accountability Act (HIPAA), you have to ensure that your data processing and sharing do not violate the rights and interests of the data subjects. Data masking and anonymization can help you reduce the risk of data breaches, fines, or lawsuits, as well as maintain the trust and reputation of your organization.

3 What are the types of data masking and anonymization tools?

Data masking and anonymization tools are software applications or services that can help automate and simplify the process of data masking and anonymization. Depending on their features and functions, they can be classified into different types, such as data discovery, masking, and anonymization tools. Data discovery tools can identify and classify sensitive data in data sources, based on predefined or custom rules, policies, or standards. They can also assess the risk of data exposure and provide recommendations or suggestions for masking or anonymization. Data masking tools can apply different techniques to sensitive data, such as substitution, encryption, hashing, masking, or shuffling. Additionally, they can manage and monitor the masking process and ensure the consistency and integrity of the masked data. Data anonymization tools can apply different anonymization techniques to sensitive data, such as generalization, suppression, perturbation, or aggregation. They can also measure and evaluate the effectiveness and efficiency of the anonymization process, while ensuring compliance and accountability of the anonymized data.

4 How to choose the best data masking and anonymization tools?

When it comes to data masking and anonymization, there is no one-size-fits-all solution. Different tools may have different strengths and weaknesses, and different use cases may have different requirements and preferences. To compare and evaluate different data masking and anonymization tools, look for compatibility with your data sources, formats, platforms, and environments; functionality such as data discovery, data masking, data anonymization, data quality, data management, data monitoring, data reporting, or data auditing; performance in terms of speed, scalability, reliability, and accuracy; usability in terms of user-friendliness; and security in terms of protection from unauthorized access or modification. All of these criteria should be taken into account when considering which tool to use.

5 What are some examples of data masking and anonymization tools?

Data masking and anonymization tools can be found in abundance, each with its own benefits and drawbacks. Popular or potentially promising tools to consider include IBM InfoSphere Optim, Oracle Data Masking and Subsetting, Delphix Data Platform, ARX, and Privitar. IBM InfoSphere Optim provides data management features such as data discovery, masking, anonymization, quality, governance, and lifecycle management. It supports various data sources and masking techniques like substitution, encryption, hashing, masking, shuffling, generalization, suppression, perturbation or aggregation. Oracle Data Masking and Subsetting offers data security features such as discovery, masking, subsetting, quality and auditing. It supports various data sources like Oracle databases or non-Oracle databases or files with masking techniques like substitution, encryption, hashing, masking or shuffling. Delphix Data Platform is a data platform that provides features such as discovery, masking and virtualization as well as delivery and governance. It supports various data sources with masking techniques like substitution, encryption, hashing or tokenization. ARX is a data anonymization solution with features such as discovery, anonymization and risk management that supports various data sources like databases or streams along with anonymization techniques like generalization or suppression. Lastly Privitar is a data privacy solution that provides features such as discovery and protection with generalization or aggregation for anonymization. All these tools provide graphical user interfaces along with command-line interfaces or APIs for their respective functions.