Data masking is also known as data obfuscation.
The existing data is replicated within data masking with an inauthentic version of the same and is further made available for processes like software testing and user training.
In simple, it masks actual data by random characters, thereby safeguarding the sensitive information from people who don’t have the authorization to view it.
The aim behind data masking is to perform the functional substitutes while protecting the actual data.
Below discussed are some of the data masking tools.
FieldShield by IRI is a data masking tool.
It is mostly used by corporate and government IT bodies for masking sensitive data within the flat files, databases, and other data storage systems.
It searches for CSI, PI, PII, PHI, PAN, and other sensitive information. FieldShield allows users to de-identify such sensitive data as putting conditions on rows and data columns, encrypt with their own data library, etc.
Some of the key features of FieldShield by IRI are as under:
- PII (Personally Identifiable Information) is by default found and classified.
- Upholds security by using a state-of-art algorithm that is difficult to hack.
- Verify compliance with query ready XML audit logs.
Need to contact the sales team for Price.
iMask dynamic data masking is powered by MENTIS.
It is mainly utilized for production environments.
With iMask, enterprises can easily decide as to who is eligible for seeing masked or unmasked data.
It safeguards your production data by replicating it with fictitious data in unauthorized reports or views.
Some key features of iMask are discussed below:
- Access to sensitive information is cleared through conditional or role-based methods.
- Users can mask the data across active multiple storage devices like DBMS – Oracle, SQL Server, and Sybase in an enterprise.
- Uses proxy-based servers for protecting data in cloud-based applications.
Need to contact the sales team for pricing.
Oracle data masking and subsetting provide users with a masking library that assists in defining the mask of data.
Users can create new and multiple formats based on their requirements.
With the help of predefined formats, a user can mask sensitive information.
Some key features of Oracle are as under:
- Automates procedures with the help of application data modeling, thereby assisting in discovering sensitive information and finding relations between parent data sets and child data sets.
- Upholds security through its random shuffling procedure wherein a particular data set is shuffled with other information to break its mapping with the original one.
- Users can migrate their existing masking scripts with the help of User-defined PL/SQL Masking.
Oracle data masking and subsetting are available under two metrics:
- Named user plus: Users get charged US $230/Named user plus for this plan.
- Processor: Users are charged US$ 11,500/Processor under this plan.
For updating the software license and software support, users will be charged US $2,530.00 in the first year.
Dynamic data masking by Informatica is installed between applications and databases.
All of the inbound requests from the application are processed with the proxy’s help, which screens the data collected from reports and tools.
After a request has been acted on, dynamic data masking forwards requests for further execution.
Some of the key features of dynamic data masking by Informatica are as under:
- It is quite scalable as it is able to assist multiple databases through a single installation.
- Alerts users whenever there is unauthorized access to the databases.
- Allows visibility to only those applications that meet the security requirements selected by the user.
After the free trial of 30 days, users need to contact the sales team for prices.
Dynamic data masking by Data Sunrise with the help of Data Sunrise database security work secures the existing database and modifies it into predefined and random data.
Users have to predefine the data entries for which data masking is to be done and have to define the location of these databases.
It also allows users to use dashboards to create masking policies.
Some of the key features of Dynamic data masking by Data Sunrise are as under:
- Users have access to the updated database always.
- Users need not be dependent on additional servers.
- As soon as the query is entered by the client, the dynamic database intercepts it and changes the responses of the database.
It offers users a free trial at the beginning but for more features, a user needs to contact the sales team.
Talend allows users to implement data masking practices through two of its products.
• Talend Data Quality: With the help of Talend data quality, a user has the advantage of putting the shuffling process into action.
With data shuffling, data privacy is done.
Data columns are randomly shuffled, which helps in keeping the actual identity of the data hidden. Values within these columns are replicated with inauthentic ones.
• Talend Data Preparation: Through Talend data preparation, data masking can be done in an ad-hoc manner.
This means that before the data is shared, the sensitive information in actual data sets is kept protected.
- Machine learning is used for addressing data quality issues.
- Users can easily profile and clean data in real-time.
- Governance of data is kept within the hands of users.
Need to contact the sales team for a price.
Dynamic data masking by Immuta assists users in masking sensitive information without even copying or moving data.
It assists users in complying with federal, industry, employment, and contractual regulations without shifting data or copying it.
Some key features of Dynamic data masking by Immuta are as under:
- K-Anonymization technique is used for the privacy of information while anonymizing data. Immuta allows the data team to apply K-Anonymization at query time from any data source within the organization helps users anonymize the sensitive data that can be further used without any legal or privacy concerns.
- Use of conditional data masking minimizing security and privacy risks by automating access based on time-based windows, user’s geography, and data in adjacent cells or reference tables.
- Uphold local differential privacy through randomized response by putting limits for attackers.
It allows users for a free trial of 14 days. After the expiration of the free trial, users need to contact the sales team for prices.
Data mask by Salesforce assists teams in testing and building applications by protecting any sensitive information.
Full sandbox mirror productions assist teams in quick testing of applications.
Sandboxes are used to run applications separately so that the source is not affected by any virus present in applications.
Data mask protects sensitive data within sandboxes without fetching data out from the Salesforce platform.
Some key features of Data mask by Salesforce are as under:
- Users can secure their sensitive data through pattern-based masking wherein masking configurations are generated with random letters or digits of 20 characters.
- With server-side pre-processing, users with increased speed can allow other processes to run in parallel, and within this, they need not be active on different browsers for data masking.
- Users need not go for separate configuration masking as with a data mask they can clone an existing masked configuration having similar characteristics.
Need to contact the sales team for a price.
Also Read: 11 Best Tools for Data Governance
FileMasker by DataVeil is used for masking flat files and text files in the format of CSV and JSON.
It can also be run as an AWS Lambda function.
Some of the key features of FileMasker by DataVeil are as follows:
- FileMasker can process many terabytes of data per hour.
- Incoming file formats like CSV and JSON from S3 can be masked with the FileMasker Lambda function.
- Users can locally mask files on their file system directly from the GUI or command line.
FileMasker is available under two type of licenses:
• Community License
Community license is free and is provided to the user on signing in to their free account on their website.
All features, except the command-line and the AWS Lambda component, are made available to the users.
Masks like redact, sentences, and user value is free and can be masked for unlimited data.
Community License never expires.
• Premium License
A Premium license is free and a user can use all free and premium masks.
Premium License is further available under two options:
Under the base component users under GUI can create FileMasker masking projects.
Users under this plan can create an unlimited number of projects to mask unlimited data using every mask.
For 1 year, a user is charged an amount of $1,800.
For 2 years, charges will be $3,420.
For 3 Years, charges for users are $5,040.
For 4 years, a user will be charged an amount of $6,660.
Base + AWS Lambda component
Users receive all the benefits of the Base component with added features wherein now a user can create an unlimited number of masking projects.
For a period of 1 year, a user is charged $5,800.
For a period of 2 years, a user is charged $11,020.
For a period of 3 years, a user is charged $16,240.
For a period of 4 years, a user is charged $21,460.
Data masking by Delphix assist users in protecting sensitive data throughout enterprises through an automated approach wherein it protects data related to the non-production environment.
Focus is on sensitive information like social security numbers, patient records, and credit card information.
Such data is replaced with fictitious yet realistic data to uphold security and privacy.
However, data masking integrates efficiently with data delivery capabilities wherein sensitive data is secured at an early stage before passing it on for deployment and testing.
Some of the key features of data masking by Delphix are as follows:
- For users, it becomes easy to mask data across all platforms.
- With its end-to-end masking approach, confidential data is easily detected, masked. On completion of the same, an alert process informs users about completing the data masking procedure.
- Users can get heterogeneous data sources masked too. The foreign key relationship is identified by scanning data and metadata so that such data sets are hidden the same way across multiple tables and databases.
Need to contact the sales team for a price.
Irion assists businesses in meeting privacy and security concerns by keeping data flow consistent while addressing privacy and compliance issues.
Some key features of data masking Irion are as follows:
- Full integration of data masking with Irion platforms assists users wherein pre transformed data can be masked along with its output. Users can further avail functions like mapping dictionaries or integrating solutions with their data governing strategies.
- Users can repeatedly use the masking engines on datasets according to their needs.
- Mask your entire database at the source or mask it after the data has been accessed through applications.
Users need to contact the sales team for prices.
Data masking by Accutive assists in automating the discovery of sensitive information.
All the source fields are mapped at the time of discovery and maintained.
Output data presented after discovering and mapping the fields will still be functional, but now it will no longer be sensitive as now it was presented in a masked form.
Masked data in Accutive data masking will remain the same across all sources.
Some key features of data masking by Accutive are as under:
- Move data from any source to any major database type such as Oracle, DB2, MySQL and SQLServer.
- Mask your data within cloud environments too.
- Users have the privilege of keeping your masked source data to same value.
Accutive has presented its pricing under four packages:
Under the Starter pack, a user is charged the amount of $2000 per month.
In an Essential package, users have to pay the sum of $3500 per month.
For Professional packages, users need to pay $5750 per month.
For Enterprise packages, users will have to make contact with the sales team.
Fogger is an open-source GDPR friendly data masking tool that assists developers in complying with their production data.
Fogger provides users with the option of creating subsets and even exclude particular tables.
Moreover, users can extend Fogger with their strategies.
Some key features of Fogger are as follows:
- Easily integrates with your current infrastructure.
- Exclude data tables that re no longer in need.
It is available to users as an open source.
Data masking by BizDataX simplifies the data masking process in non-production environments by cloning the complete production or only a subset of its data.
BizDataX finds sensitive data, transforms it into the least sensitive data, and applies it to the database and further compliances with GDPR, thus improving overall business operations.
Some of the key features of BizDataX are as under:
- BizDataX upholds data integrity by making sure that the data across sources are the same.
- If users are not having production data available for testing products, this gap is filled by BizDataX with replicated or synthetic data that looks as genuine as the real one.
- It creates replaced values in the same format as that in real data subsets.
Within a trial period of 30 days, users can replicate 1TB of data size with a maximum of 100 data masking fields.
After the trial period is over users need to contact the sales team for using more advanced features.
Data Masker by Redgate provides users with an automated data masking approach.
It integrates with SQL Data catalog that assists in providing masking set for keeping sensitive data safe.
Some of the key features of Data masking are as under:
- Keeps users ready and equipped with automated masking approaches for future compliances.
- It is quite fast because of its high performing systems that enable faster data masking.
Need to contact the sales team for pricing.
The above-mentioned data masking tools are some of the best ones available in the market as of 2020.
However, selecting the right tool depends on the data size, day to day operational requirements, and other business parameters.
Organizations are expected to be cautious and should perform thorough research before opting for any data masking tool.