Data Masking is the process of replacing authentic original data with data that is structurally similar but provides fake values. this means that the original format is retained but values are changed. The change in values takes place through methods such as encryption, shuffling, substitution, etc. The process of data masking makes it nearly impossible to obtain or reverse engineer original data, hence it is a one-way process.
Many tools are available on the market that makes the tasks of Data Masking easier, this article gives the Best Data masking Tools in the market.
What is Data Masking?
Data masking, as the name suggests, is a process to create a masked version of the true version of your organizational data retaining its original aspects. The main motto is to provide a functional solution that does not contain real and sensitive data but instead provides a copy of the structure. Data masking is mainly used for software testing, product demo, or user training, where real data is not required.
Data masking retains the original structure of data and changes its values. the data produced after data masking is nearly impossible to reverse engineer or decipher. This takes place by following methods like shuffling, substitution, and encryption.
What are the Benefits of Using Data Masking?
- Prevents Critical Threats: data loss, data exfiltration, insider threats or account compromise, and insecure interfaces with third-party systems.
- Cloud Adoption: Reduces data risks associated with cloud adoption.
- Encryption: this Makes data useless to an attacker while maintaining many of its inherent functional properties.
- Reduces Exposure: Allows sharing data with authorized users, such as testers and developers, without exposing production data.
- Data sanitization: sanitization replaces the old values with masked ones since normal deletion of files still leaves traces of information.
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What are the Data Masking Techniques?
Many Data Masking Techniques are available, a few of them are mentioned below.
Data Encryption
In the process of data encryption, the data is coded and it requires a decryption key to decipher it. unless there is a key the data is meaningless. the data masking is done by an encryption algorithm. It is one of the most secure means of data masking but it is very complex to implement because it requires advanced technology to encrypt, manage and generate keys for the data.
Data Scrambling
Characters of the value in data are reorganized in random order and then replaced with the original content. For example, an ID number such as 76498 in a production database, could be replaced by 84967 in a test database. This method is very simple to implement, but can only be applied to some types of data, and is less secure.
Nulling Out
When an unauthorized user tries to access the data it shows “null” or missing. this makes data less useful to use for development and testing purposes
Value Variance
The real values of the data are replaced by values of any function like the lowest and highest values, mean values, or any other function. For example, if a customer purchased several products, the purchase price can be replaced with a range between the highest and lowest price paid. This can provide useful data for many purposes, without disclosing the original dataset.
Data Substitution
Data values are substituted with values that belong to a realistic range similar to the real values, For example, real customer names are replaced by a random selection of names from a phonebook.
Data Shuffling
It is similar to substitution, but the data is shuffled from the data. this means that original data is present in masked data but it is shuffled. Data is rearranged in each column using a random sequence; for example, switching between real customer names across multiple customer records. The output set looks like real data, but it doesn’t show the real information for each individual or data record.
What are the Types of Data Masking?
Follow along to understand the various types of data masking.
1) Static Data Masking
Static data masking techniques assist you in creating a clean replica of the database. The method modifies all sensitive data at rest until a copy of the database can be safely shared. This process creates a backup copy of a production database, loads it to a separate environment, removes any extraneous data, and then masks data while it is static. The masked copy can then be delivered to the desired location.
It is utilized to deliver high-quality (realistic) data for application development. Static data masking can be performed using ETL-like solutions or technologies that can perform it directly within the database.
2) Deterministic Data Masking
Deterministic Masking is the process of mapping two values so that one value in a column is replaced with the same value whether in the same row, table, database/schema, or instance/server/database type.
This approach is useful in many situations, but it is generally less secure.
3) On-the-Fly Data Masking
On-the-Fly Data Masking occurs throughout the process of transporting data from one environment to another without the data touching the disk along the way. T When necessary, this method sends smaller subsets of masked data whenever required. Each subset of masked data subset is saved in the development/test environment for usage by the non-production system.
To avoid compliance and security difficulties, it is essential to apply on-the-fly masking to any feed from a production system to a development environment at the start of a development project.
4) Dynamic Data Masking
This masking procedure is identical to on-the-fly masking, with the exception that data is never stored in a secondary data store in the development/test environment. It is instead streamed directly from the production system and ingested by another system in the development/test environment.
This masking procedure aids in the prevention of unwanted access to sensitive data by allowing customers to select how much sensitive data to reveal while minimizing the impact on the application layer.
Here are the twelve top data masking tools:
Follow along to understand comprehensively about every tool that makes the data masking tools list.
1) Data Masking Tools: DATPROF
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DATPROF Data Masking tool provides a smart way of masking and generating data for testing the database. It has patented an algorithm for subsetting the database efficiently.
The Data Masking tool is able to handle complex data relationships with an easy-to-use interface. It has a really smart way to avoid all triggers, constraints, and indexes so it is the best-performing tool in the market.
Features:
- Consistent over multiple applications and databases.
- XML and CSV file support.
- Built-in synthetic data generators.
- HTML audit / GDPR reporting.
- Test data automation with REST API.
- Web Portal for easy provisioning.
Pros:
- High performance on large data sets.
- Free trial version available.
- Easy to install and use.
- all major relational databases are natively supported.
Cons:
- English documentation only.
- Development of templates requires Windows.
- Execution of templates can be done on Windows or Linux.
Learn more about DATPROF.
2) Data Masking Tools: IRI FieldShield
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The IRI FieldShield data masking tool is popular in the DB data masking and test data market due to its fast, low cost, compliance capabilities, and various data sources supported. It is compatible with other IRI data masking, testing, ETL, Eclipse data quality and analysis jobs, SIEM tools, and Erwin platform metadata.
Features:
- Profiling, detection (searching), and classification of data from multiple sources.
- A wide range of masking features (including FPE) for anonymizing and anonymizing PII.
- Referential integrity across schemas and multi-DB / file scenarios.
- Built-in reID risk assessment and audit trails such as GDPR, HIPAA, PCI DSS.
Pros:
- High performance that does not require a central server.
- Simple metadata and multiple options for graphical job design.
- Works with DB Subset, Synthesize, Reorganize, Migrate, ETL Jobs, and Key DB Cloning, Cryptographic Key Management, TDM Portal, and SIEM environments in Voracity.
- High-speed support and affordability (especially compared to IBM, Oracle, and Informatica).
Cons:
- 1NF only supports structured data.
- Dark Shield is required for BLOB etc. The free IRI Workbench IDE is a client Eclipse UI (not web-based).
- The DDM requires a FieldShield API call or a premium proxy server option.
Pricing: Free trial & POC help. Low 5-figure cost for perpetual use or free in IRI Voracity.
Learn more about FieldShield
3) Data Masking Tools: Accutive Data Discovery & Masking
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Accutive’s Data Masking Tool (ADM) provides the ability to detect and mask sensitive data while ensuring that data properties and fields remain intact across any number of sources.
Data Discovery allows you to efficiently identify sensitive data based on preconfigured editable compliance filters or user-defined search terms. You can feed the data detection results to the data masking configuration or define your own. Even after being processed by the
masking operation, the data is still visible, but fictitious. Masked data is also consistent across all sources.
Masking production data for non-production applications reduces the risk of data breaches while helping to meet regulatory requirements.
Features:
- Data Detection – Enables efficient identification of sensitive data that must meet regulatory compliance standards such as GDPR, PCI DSS, HIPAA, GLBA, OSFI / PIPEDA, FERPA.
- Mask Link Technology-The ability to consistently and repeatedly mask source data to the same value across multiple databases (that is, Smith is always masked by Jones).
- Multiple Data Sources and Destinations-Data can be moved from any major source type to any major destination type such as Oracle, DB2, MySQL, SQLServer (for example, data moved from a flat file to an Oracle database). I can do it).
- API support-Include data masking in your data processing pipeline.
Pros:
- User-friendly and configurable interface.
- A cheap solution with a transparent pricing model.
- Use the built-in progress bar to quickly perform masking configurations.
Cons:
- Groovy scripts for customizing the behavior of applications require programming knowledge.
- Currently not available in languages other than English, French, Spanish, and German.
Pricing: Four packages are available dependent on customer needs. Contact them for more details.
Learn more about Accutive
4) Data Masking Tools: Oracle Data Masking and Subsetting
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The Oracle Data Masking and Subsetting Data Masking tools provide database customers with the benefits of increased security, faster delivery, and lower IT prices.
Helps remove duplicate data testing, development, and other actions by removing redundant data and files. This tool suggests a plot of the data and uses the masking instructions. This includes HIPAA, PCI DSS, and PII-encoded policies.
Features:
- automatically recognizes complex data and their relationships.
- Wide masking plan library and extended application model.
- Full data masking revolution.
- fast, safe, and sorted.
Pros:
- suggests various data masking habits.
- Supports non-Oracle databases.
- The execution time is reduced.
Cons:
- High cost.
- The security of the development and test environment is reduced.
Pricing: Contact for Pricing.
Learn more about Oracle Data Masking
5) Data Masking Tools: Delphix
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Delphix Data Masking Tool is a fast, secure and one of the top open source data masking tools for masking data across your enterprise. This includes HIPAA, PCI DSS, and SOX-encoded rules.
The Delphix Masking Engine, in combination with the Delphix Data Virtualization Platform, saves and saves data loads. DDM exists through a partnership with Hexa Tier.
Features:
- End-to-end data masking and reporting.
- Masking In combination with data virtualization to facilitate data transfer.
- Easy to use as no training is required to mask the data.
- Continuously migrate data between sites, on-premises, or in the cloud.
Pros:
- Restore recordings easily and quickly.
- Database virtualization.
- Data update is fast.
Cons:
- High cost.
- SQL Server database is slow and limited.
- Depends on the legacy NFS protocol.
Pricing: Contact for pricing.
Learn more about Delphix
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Informatica Persistent Data Masking Tool is an accessible data masking
The Informatica Persistent Data Masking Tool is an easily accessible data masking tool that helps IT organizations access and manage the most complex data.
Provides enterprise scalability, robustness, and integrity for a large number of databases. Use a single audit track to create reliable data masking rules across the industry. Allows you to track actions taken to protect sensitive data through complete audit logs and records.
Features:
- supports robust data masking.
- Build and integrate the masking process from a single location. The
- works to handle large databases.
- Provides extensive connectivity and customized application support.
Pros:
- Reduces the risk of data breaches through a single audit trail.
- Improve the quality of development, testing, and training events. Easy deployment on workstations.
Cons: Requires more user interface work.
Pricing: A 30-day free trial is available.
Learn more about Informatica Persistent Data Masking
7) Data Masking Tools: Microsoft SQL Server Data Masking
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The Dynamic Data Masking Tool is a new security feature announced at SQL Server 2016 that controls unlicensed user access to complex data.
This is a very simple and easy protection tool that you can build using TSQL queries. This data security method detects complex data through fields.
Features:
- This facilitates application design and coding by protecting your data.
- Do not modify or convert the data stored in the database.
- This allows the data steward to choose the level of complex data to expose with less impact on the application.
Pros:
- End operators should not visualize complex data.
- Generating a mask for a column field does not prevent the update.
- No application needs to be modified to read the data.
Cons:
- Full access to data while the table is queried as a privileged user.
- You can remove masking via the CAST command by running an ad hoc query.
- Masking cannot be applied to columns such as Encrypted, FILESTREAM, COLUMN_SET.
Pricing: Free trial is available for 12 months.
Learn more about Dynamic Data Masking
8) Data Masking tools: IBM InfoSphere Optim Data Privacy
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The IBM InfoSphere Optim Data Privacy data masking tool proposes data mappings and uses masking reports with masking objects. There are predefined reports for PCI DSS and HIPAA.
This offers comprehensive possibilities for efficiently masking complex data in non-production environments. To protect your personal data, this tool replaces sensitive information with true and completely useful masked data.
Features:
- Masks private data on request.
- Lock data to mitigate risk.
- Attach the privacy application.
- Safe environment for application testing.
Pros:
- Just abstract the data without encoding.
- Extended data masking function.
- Smart filtering function.
Cons:
- Requires work with the user interface.
- Complex architecture.
Pricing: Contact for Pricing.
Learn more about IBM InfoSphere Optim Data Privacy
9) Data Masking Tools: CA Test Data Manager
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CA Test Data Manager‘s data masking tools comply with the General Data Protection Regulation (GDPR) and other laws to help with privacy and compliance issues.
This tool provides data mapping, data movement, and functional masking. There are universal file reports and metadata. We have SDM expertise for complex, large-scale environments with a consistent database.
Features:
- Create synthetic test data for data tests.
- Create future test scenarios and unexpected results.
- Save data for reuse.
- Make a virtual copy of the test data.
Pros:
- Various filters and templates are available to mask data.
- No additional permissions are required to access production data.
- Very fast data masking tool.
Cons:
- Works only on Windows.
- Complex user interface.
- It’s not easy to automate everything.
Pricing: A Free trial is available.
Learn more about CA Test Data Manager
10) Data Masking Tools: Compuware Test Data Privacy
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Compuware Test Data Privacy helps in the mapping of data and generic masking reports.
This data masking tool mainly works on the mainframe platform and supports hybrid non-mainframe settings. Their solution offers Topaz for Enterprise Data for reliability, conversancy, and security.
It has two essential areas to perform test data privacy solutions for securing test data i.e. data breach prevention and compliance with data privacy laws.
Features:
- Decreases the difficulty by codeless masking.
- Completes data normalization into and out of the masking process.
- Dynamic Privacy Rules with complex test data essentials such as account numbers, card numbers, etc.
- Allows to discover and mask data within a greater field.
Pros:
- Easy to use and is fast.
- Secures test data against breaks.
- Apply test data privacy to test data, so that it will be more secure.
Cons:
Pricing: Contact for Pricing.
Learn more about Compuware Test Data Privacy
11) Data Masking Tools: NextLabs Data Masking
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NextLabs Data Masking tool offers an established software that can shield data and guarantee compliance in the cross-platform.
The essential part of NextLabs data masking is its Dynamic Authorization technology with Attribute-Based Access Control. It secures all critical business data and applications.
Features:
- Helps in classifying and sorting data.
- Monitors data movement and its usage.
- It prevents access to precise data.
- Notifications on risky actions and irregularities.
Pros:
- Can be installed easily in each workstation.
- Evades data breaking.
- Data Safety across CAD, PLM, and email is good.
Cons:
- Software compatibility problems with PLM software.
- Execution is tough at times for the suppliers and vendors.
Pricing: Contact them for pricing.
Learn more about NextLabs Data Masking
12) Data Masking Tools: Hush-Hush
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The Hush-Hush data masking tool shield helps in recognizing data against internal risk.
It de-identifies the establishment’s complex data. HushHush elements are out-of-the-box procedures that are built for elements such as credit cards, addresses, contacts, etc.
This data masking tool de-identifies data in folders, records, emails, etc., through API. Its custom code can be planned and ad-hocked.
Features:
- Less time and Easy installation.
- Supple, Robustness and takes less time to create workflows.
- Easy and Robust Combination into SQL server, Biztalk, etc.
- Custom SSIS agenda to mask data.
Pros:
- Speed up development.
- No learning curves.
- Create data with just the “INSERT” command.
Cons:
- In startups the growth is fast but progress slows down in developed industries.
- Limited control of data.
Pricing: You may request free use and contact them for final pricing.
Conclusion
This article gave a comprehensive guide on Data Masking and Data Masking Tools.
Since Data masking is an important aspect of protecting data, Having a solution that provides secure ETL and data pipeline is important and that is where Hevo comes into the picture. Hevo Data is a No-code Data Pipeline and has awesome 100+ pre-built Integrations that you can choose from.
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Hevo can help you Integrate your data from numerous sources and load them into a destination to Analyze real-time data with a BI tool such as Tableau. It will make your life easier and data migration hassle-free. It is user-friendly, reliable, and secure.
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Share your experience of learning about top data masking tools in the comments section below.
Arsalan is a data science enthusiast with a keen interest towards data analysis and architecture and is interested in writing highly technical content. He has experience writing around 100 articles on various topics related to data industry.