Preventing Fraud: The Advantages of Adaptive Authentication
What Is Adaptive Authentication?
Adaptive authentication is the process of authenticating a user based on the risk level presented by a login attempt. An essential component of adaptive authentication is the use of multi-factor authentication. Typically the risk level is assessed automatically by the first authentication method, and if the fraud risk is low, the login is granted. If the risk is high, step-up authentication is triggered and the user is asked for another type of authentication. Ideally, the first authentication method used in an adaptive authentication flow should present the lowest friction for users. In this way, the majority of users, who are legitimate, will be able to log in easily. Higher friction authentication methods will be used as additional steps for the users that were flagged as high-risk in the initial login attempt. Since risk is the defining factor to determine the ease for the user to log in, adaptive authentication is also referred to as risk-based authentication.
Methods to deploy Adaptive Authentication
There are several methods to implement adaptive authentication. Usually, the first authentication method, which could authenticate the user continuously, has to identify if there is an anomaly in the user login credentials or behavior. An anomaly could be an incorrect password or different location, device, or behavior from what is usual for the user in question.
Today location is most often determined by either the IP address or GPS but increasingly location behavior based on a combination of WiFi, Cellular and GPS signals is being used to identify location behavior patterns with a high degree of accuracy in both outdoor and indoor. If the location of the user trying to login does not match other previously identified locations, where the user usually is when in other login sessions, then step-up authentication, such as an authenticator app or face recognition would be required as part of adaptive authentication. The main differences between the location technology methods are the level of precision and accuracy and also resistance to spoofing. IP address and GPS can easily be faked or spoofed, while a more sophisticated location behavior technology cannot be spoofed.
Another possible adaptive authentication scenario is when a new device is detected at login. It could either be the user actually trying to change their device, or a fraudster trying to log in with stolen credentials from a new device. In this case, step-up MFAcould makes use of a recognition signal, such as location behavior to assess the risk associated with the login. If the user is not only using another device but is also at a completely different location that does not match with the user’s usual location behavior pattern, this can be flagged as high risk. In this case, a second authentication method could be triggered, such as a mobile push notification or requesting the use of an authenticator app, or anything that verifies the previously used device as a token of the user's possession.
These are only two among many possible examples of combinations of authentication methods to deliver adaptive authentication using both multi-factor and step-up authentication.
For further information on when each type of authentication would be used please read step-up authentication vs. multi-factor authentication.
How Does Adaptive Authentication Work?
The first thing that should be done when determining risk-based authentication solutions is defining the parameters that users will be held to when logging into the system. As users attempt to gain access to systems, they will be assigned a risk factor score. These scores are important because, depending on what they are: low, medium, or high, the user will need to provide more information before the system can authenticate their identity.
Authentication and authorization are two main steps in the security of a system. The risk score is part of the authentication part of the process. In any risk-based authentication solution, such as adaptive authentication, if the first method of authentication does not identify the user, automatically that login presents a higher risk. Additional authentication methods can provide a risk score, ranging from low to high.
The authorization then would come into play to provide usually three outcomes to that authentication attempt:
- Allowed access
- Denied access
- Challenged to provide additional information (step-up authentication)
Benefits of Adaptive Risk-Based Authentication Solutions
When it comes to adaptive risk-based authentication, there are several benefits for companies and users.
With the looming fear of fraud taking place, a company might face the temptation to force users to jump through more authentication hoops. This can lead to frustration and users abandoning their session before they've completed their transaction in the system.
With the technology available today, users can face a lot less friction, or even zero-friction on their login using adaptive authentication. By adapting the authentication method based on the risk level, lower risk methods can be used initially, saving the highest friction authentication methods for the higher risk logins. Recognition signals from sensors on the device can provide insights on mobile user behavior and device intelligence without requiring any action by the user. Working in the background these types of recognition signals enable a seamless experience for the user, where they might not even realize they are being continuously authenticated. Zero-friction also can be accompanied by high security, since there are many methods that could recognize such users, with mobile recognition signals being only one of the possible examples.
Risk-based authentication can provide lower false-positive rates for companies, which can result in higher revenue since more users are provided with a better experience and complete more transactions. Also, an adaptive authentication approach can result in a higher quality of defense against fraudsters.