Table of Contents

    Table of Contents

    Data Masking Tools List for 2024

    Data Masking Tools List for 2024
    Amitai Richman

    Amitai Richman

    Product Marketing Director

    If you’re in the market for a data masking tool to protect PII and enforce compliance with data privacy regulations, check out this list before deciding.  

    Data Masking Tools: What and Why? 

    Data masking tools are software products that protect sensitive data by creating a version of the confidential information that can’t be re-identified. Purpose-built data masking tools (provided by leading data masking vendors) retain the relational context of the data to ensure both referential integrity and data usability.  

    The most frequently masked types of data include: 

    PII (Personally Identifiable Information), such as names, addresses, phone numbers, passport numbers, and Social Security Numbers 

    PHI (Protected Health Information), such as medical records, insurance claims, and payment histories to healthcare providers 

    PCI-DSS (Payment Card Industry Data Security Standard) data, such as credit and debit card transactions and statements 

    Data masking solutions enable enterprises to:

    • Ensure compliance with consumer protection laws like GDPR (in Europe), CPRA (in California), LGPD (in Brazil), and HIPAA (worldwide). These privacy regulations are central to highly regulated industries like financial services and healthcare and require that organizations safeguard Personally Identifiable Information (PII) and other sensitive data like financial and medical records.

    • Protect data from insider threats from employees and third-party contractors. These people have regular access to production enterprise systems that often use sensitive information for development, testing, and other pre-production activities.  

    • Shield data from external threats like cyberattacks, which target sensitive data in both production and non-production environments. By masking data, organizations protect PII, preserve utility, and reduce the risk of exposing sensitive data during large data projects, like cloud migrations or third-party app integrations.

    • Maintain data governance by controlling access to sensitive data. Dynamic data masking controls data access based on roles and permissions, ensuring that only individuals with the appropriate access rights have access to the real data. This is an up-and-coming capability to look out for. 

     Get Gartner’s market guide for data masking for free.

    Data Masking Tools: List of Techniques 

    Data masking techniques protect sensitive information by disguising it, or by replacing it with realistic yet fictitious data (as a more advanced capability). These methods obscure the identifiable elements in data, maintaining privacy while allowing safe data usage for testing, analytics, or sharing. Some of the most popular data masking techniques include:

    1. Pseudonymization 

      Pseudonymization is a form of data anonymization in which codes, or pseudonyms, are substituted for the PII in a dataset. 

    2. Nulling out 

      In the context of data masking, nulling out is the process of replacing PII with null (or empty) values to safeguard privacy and comply with consumer protection laws. 

    3. Redaction 

      Redaction is a method that selectively edits sensitive data or replaces it with generic values in development and testing environments.  

    4. Shuffling 

      Shuffling is a technique that randomly reorders datasets (such as a list of telephone numbers) instead of replacing the real data with generic values.  

    Data Masking Tools: List of Challenges 

    In a dynamic business and regulatory landscape, organizations using data masking face many challenges. A key challenge is ensuring that masked data retains the basic characteristics of the original data to maintain functionality in use cases such as software testing.  

    Another challenge is the complexity and scale of enterprise IT environments, deployed both on-prem and in the cloud. To effectively mask these huge volumes of data, enterprise-grade data masking tools must be able to:

    • Handle both structured and unstructured data masking, at scale 

    • Discover all sensitive data, across all systems, automatically

    • Maintain referential integrity of all masked data, across all systems  

    • Control data access based on user-defined rules

    Data Masking Tools: List of Vendors 

    1. K2view 

      K2view data masking technology is ideal for enterprises with complex data environments. It automatically discovers PII across databases, masks it in-flight via one of many different built-in masking techniques and produces clear reports for auditing. On peer review sites, international enterprises rate K2view as rich in functionality and features. 

    2. Accutive 

      Accutive Data Masking shields sensitive data without compromising its usefulness for essential business operations. It's essentially a protective layer that makes data look genuine while ensuring that the sensitive parts are hidden across all databases. It integrates with MySQL, PostgreSQL, and SQL Server. 

    3. Hush-Hush 

      Hush-Hush data masking tools are easy to install, enabling users to establish workflows using a discovery tool. These solutions are used for outsourcing, training, testing, development. Hush-Hush integrates with native SQL server SSIS, Biztalk, and code via API. 

    4. Immuta 

      Immuta is known for its dynamic data masking policies that cover a range of techniques like hashing, conditional masking, and regular expressions – ensuring data security without having to copy or relocate information. The company uses proprietary Privacy-Enhancing Technologies (PETs) to safeguard the confidentiality of sensitive data. 

    5. IRI FieldShield  

      IRI FieldShield, from the Innovative Routines International (IRI) Data Protector Suite, is a budget-friendly data masking tool. Covering both static and dynamic data masking for structured data (only), FieldShield is said to comply with HIPAA, DPA, GDPR, CIPSEA, FERPA, GLBA, PCI DSS and other data privacy standards. 

    6. MS SQL Server Data Masking 

      Microsoft SQL Server Dynamic Data Masking (DDM) shields sensitive data by restricting its visibility without altering the database. It selectively hides specific fields in query outcomes and supports full or partial masking. Tailored for SQL Server 2016 (13.x) and Azure SQL Database, it’s configurable via Transact-SQL commands. 

    Why K2view is #1 on the Data Masking Tools List

    Entity-based data masking from K2view tops the data masking tools list because Gartner lists K2view as a visionary in its 2023 magic quadrant.  

    K2view maintains referential integrity and ensures consistent and comprehensive masked data. With PII masked in flight, the solution supports dynamic data masking for operational scenarios, along with static data masking for software testing and analytics workloads.

    With K2view data masking tools, enterprises can ensure that their production, testing, and analytics teams can access the data they need, without risking a security breach or non-compliance with privacy laws – all thanks to the company’s patented business entity approach.

    Learn more about K2view entity-based data masking tools. 

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