iDiscover is the MENTIS suite’s solution for data discovery allowing you to discover data across a wide variety of data sources and formats, including big data. It also offers several distinct methods for classifying data. For example, matching known column and table names against a data dictionary, pattern matching, classification of discovered data by comparing it to known data, by validating it against rules particular to each data type, and even by examining underlying database and application code.
iScramble allows you to apply a variety of masking methods to your data while maintaining referential integrity. Data can be masked where it is stored and updated in place or you can mask data in-transit while files are being transferred between systems, and there is also an “as it happens” option based on triggering masking when new data is added. iScramble can also be combined with iMask for a combination of static and dynamic masking. Unlike static data masking, dynamic data masking applies masking rules to data as it is accessed, depending on the privileges of the user or program attempting to access it. A major feature is that you can apply conditional masking, the ability to mask – or mask in a certain way – depending on the context. This may be combined with location-aware masking, which is the ability to mask data (or not) depending on the physical location of the user or program attempting to access it. iMask also supports encryption and tokenisation as well as masking per se. It works by allowing you to create masking templates consisting of masking rules and associated data and metadata. Deployment can be via a proxy server, or file server, or embedded in a database or application.
MENTIS uses iMonitor to provide monitoring, complete with a decision and alerting engine. This leverages template schemas, generated by iDiscover (if you’re using it) during the discovery process, to monitor the different data types within your system. In particular, it provides user activity monitoring that tracks user logins and connections to your various data sources and statements: monitoring logs, programs, and data being accessed, in near real-time. Finally, iRetire is a data retention product within the MENTIS suite that specialises in retiring your data: archiving it (tokenised) or otherwise removing it from your system at the end of its lifecycle. It leverages the same template schemas – again generated by iDiscover – as iMonitor, allowing you to create data retention rules that act on pre-specified tables and columns within your database (potentially with added conditions, such as a user ID) to retire the data contained within them.
All the MENTIS products are implemented using an Oracle database (hosted on-premises) with a Tomcat application server and agents running on relevant databases and file servers (either on-premises or in the cloud). The engine doesn’t store any data (and, in particular, sensitive data) in and of itself, but it does hold metadata. Both structured and unstructured data are supported. In fact, one of the biggest advantages offered by MENTIS is the ability to handle a wide range of data – on-premises, in-cloud, structured, and unstructured – consistently and within the same platform.
