Privacy Enhancing Technologies
Secure data-in-use with the help of our context and format preserving anonymization methods that ensures security of the data while retaining its usability and preserving the data value.
Unlock the power of your data without compromising security or privacy
- Anonymize sensitive data using context and format preserving anonymization techniques.
- Retain the value of your data while mitigating risk of sensitive data exposure
- Secure your data using robust anonymization methods that minimizes the risk of re-identification
Perform secure testing and analytics on your data
- Use differential privacy techniques to secure sensitive data while retaining data usability
- Mimic production data in your non-production and testing environments without exposing sensitive data
- Synthetically generate realistic data that is identical to your production data
With Mage organization have access to a solution that offers:
- Determine the likelihood of the discovered data classification being sensitive data with a scorecard approach, that assigns confidence scores
- Choose from three scan types, namely Sample Scan, Full Scan, and Incremental Scan, with flexible scanning methods
- Scan only the newly added tables/rows/columns after a datastore refresh through incremental scanning
Privacy Enhancing Techniques
- Anonymize your data through mechanisms that not only preserve the format of the original data, but also retains the context
- Generate realistic data for analytics and testing that replicates production data without the inherent risk of sensitive data exposure
Encryption, Tokenization, and Masking
- 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 the best-in-class security for your sensitive data with NIST approved fips140
algorithm for encryption and tokenization.
Minimal risk of re-identification
- Enable adequate anonymization with minimal re-identification risk using MENTIS Identities (patent pending) masking method.
- Generate a fake dataset similar in characteristics to the original data through fuzzy logic and artificial intelligence, with MENTIS identities.
- Maintain an anonymized datastore that preserves demographics, gender ratios, age distribution, etc.
Overall Capablity Score
“iMask has met all of our expectations”
IT Domain Manager, Security & Risk Management
Firm Size: 30B+ USD
“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.”
“Artificial intelligence to uncover data in the most complex of locations”
Project Manager, Product Management
Firm Size: 10B-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.”
“Really helpful in protecting most sensitive data elements”
Decision Analyst, Data and Analytics
Firm Size: 1B-3B 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.”