Using behavioral biometrics to provide an extra layer of security to PIN based authentication
There are countless statistics that highlight the fact that many individuals reuse the same PINs and passwords across their online accounts. All it takes is for a fraudster to get hold of a user’s details for one account and relay those across a multitude of other sites. As customers increasingly look to adopt mobile first journeys for banking, payments and online browsing, institutions need to ensure that the right layers of security are in place. With one-timepasswords/PINs being one of the most common methods of two-factor authentication, it’s important that these methods are as secure as they can be.
Using state of the art machine learning techniques, we can verify that mobile device usage is unique to an individual, presenting novel ways to apply behavioral biometrics as a form of identification. By building an understanding of user behavior overtime, we are able to prove identity with a greater degree of accuracy, rather than relying solely on static authentication that traditional biometrics and knowledge-based authentication brings.
This whitepaper looks at how mobile device usage is unique to an individual and is near impossible to replicate. Such as how the device is used and the user's ergonomic behavior whilst inputting a PIN.