Version 2.0.1 supports Credit Card Extraction

Credit-Fraud-Detection-MethodsIn November we have released version 2.0.1 of Tracks Inspector. In addition to many improvements to existing functionality and new extensions to our API, this version now includes automatic detection of credit card numbers. Tracks Inspector uses this information to create a new content facet filter that distinguishes between Context and Context Name. In this case Context is credit card and Context Name is Visa, MasterCard, Amex etc.


Credit Card Numbers

Credit card numbers are 16 digit numbers which follow a pattern. For instance the first one or two digits can be used to distinguish the issuer, e.g. Visa=5, MasterCard = 51, 52, 53, 54 or 55, American Express = 34 or 37 etc. To avoid mistakes the 16th digit in a credit number is a so-called check digit. The Luhn algorithm (see below under more reading for a reference) calculates this check digit using the first 15 digits as input. It is a clever algorithm that typically credit card writing errors, e.g. writing one digit wrong, changing the order of two consecutive digits etc.

Smart extraction, filtering and analytics

During processing, Tracks Inspector will not only check for 16 digit numbers with a valid issuer prefix, it will also perform the last digit check using the Luhn algorithm. This avoids many false positives. The extracted numbers for a document are stored in the database and are used to enable the user to filter documents and emails using the Context and Context Name facets. We will keep adding other contexts to Tracks Inspector such as car license plate numbers, social security numbers etc. We will add new dashboards that enable users to quickly discover evidence units that contain credit card numbers.

Other enhancements in version 2.0.1

In addition to credit card extraction version 2.0.1 also brings other improvements. For instance, caching of the gallery views has changed to speed up review of pictures, emails, documents etc. The v2.0 API has been further extended and documented. We have implemented the facet filtering in a vertical side bar on the left side of the screen because during interviews as part of the DED project workshop participants commented they felt that was more natural. Our demo server is running version 2.0.1 so get your free demo account to check out these new features.

More reading

  • For a more detailed description on the Luhn algorithm check for instance the following blog on DataGenetics