Protect your sensitive data by balancing performance and security. Pick the anonymization method of your choice, including encryption, tokenization and masking.
Secure data in Pre-Production and Non-Production environments
- Choose from 60+ different anonymization methods to protect your sensitive data effectively
- Maintain referential integrity between applications through anonymization methods that give you consistent results across applications and datastores
- Anonymization methods that offer you the best of both worlds in terms of protection and performance
- Choose to encrypt, tokenize, or mask the data according to the use case that suits you
Demonstrate compliance with Privacy Regulations
- Anonymize your sensitive data using a range of methods that provide adequate security while maintaining data usability
- Protect sensitive data across data stores and applications and maintain referential integrity between them
- Choose from a variety of NIST-approved encryption and tokenization algorithms in addition to masking
- Maintain minimal reversibility risk, thereby complying with rigorous regulations like HIPAA, GDPR, and CCPA
Maintain a secure environment for your sensitive data through an Anonymization solution
Encryption, Masking and Tokenization
- Choose how you want to secure your sensitive data with a data classification centric anonymization technique
- Secure your data across the spectrum, whether it is in-transit, at-rest, or in-use
- Provide best-in-class security for your sensitive data with NIST approved FIPS 140 algorithm for encryption and tokenization
Preserve data context while integrating with DevOps
- Implement masking that integrates easily with your replication process, with a choice of in-app or API based execution of anonymization
- Anonymize your data with context preserving techniques that enable you to retain data usability
- Retain the characteristics of the original data with anonymization techniques that maintain format, length, and context
Minimal risk of Re-identification
- Enable adequate anonymization with minimal re-identification risk through the use of Mage Identities (patent pending) masking method
- Generate a fake dataset similar in characteristics to the original data through fuzzy logic and artificial intelligence, with Mage identities
- Maintain an anonymized datastore that preserves demographics, gender ratios, age distribution, and the like
Unstructured Data Discovery
- Utilize the power of Artificial Intelligence and Natural Language Processing that can understand the context and discover sensitive data in unstructured fields.
- Discover sensitive data even in log files that could otherwise go undiscovered.
“I like this tool because with its secure anonymization technologies the performance and efficiency is not compromised. I like to use it because it works fast, takes a short time to run, and doesn’t use a lot of system resources. It cleans copies of our production data for testing, development, and other activities and fully eliminates unnecessary data. Our main motivation for using this solution was to achieve dynamic data masking and data protection and it never disappointed us and we are convinced that we made the right decision. iMask has perfectly met all of our expectations thus far that other tools are unable to do, we also look at a few different options, but iMask is the best.”
IT Domain Manager, Security & Risk Management
Firm Size: 30B+ USD
“Mentis helps the organization to uncover the hidden sensitive data locations within the organization with Sensitive Data Discovery module. This type of discovery is unique to the application. It uses the artificial intelligence to uncover data in the most complex of locations. It also has all compliance with popular data classifications by global privacy regulations includes the GDPR, CCPA, HIPAA. An overall recommended data masking application for the company.”
Project Manager, Product Management
Firm Size: 10B-30B USD
“iScramble is a great data masking technique that provides flexibility to encrypt data to protect it from attacks and threats. It has various anonymization techniques that help to safeguard data in non-production environments. It can source data from various applications and third party like Big Data, Hive, Oracle. It helps protect data at enterprise and database layers and help secure data on any cloud platform. This provides a complete security solution with proper masking techniques to protect data from outside attacks. Overall, it is really helpful in protecting most sensitive data elements.”
Decision Analyst, Data and Analytics
Firm Size: 1B-3B USD
Data Sources Supported
For a leading healthcare company in the US, we implemented automated static data masking to secure PHI data in Oracle.
Non-production databases are a goldmine of sensitive data and are regularly used in application development and testing. iScramble protects sensitive data in your nonproduction environments.…
This is a case study of a successful implementation of sensitive data discovery and masking. Download to read more.