Shift to Adaptive Authentication

You all must have heard the terms two-factor authentication and multi-factor authentication used for improving security and protecting web login and accounts from malicious attack and data breaches. However, organizations are seeking something better to ensure higher user-satisfaction rate along with the stronger security for their web assets. Adaptive authentication is an advanced and excellent methodology for authenticating users based on machine-learning and data analytics to deliver greater user-experience in addition to reliable security.

What is Adaptive Authentication?

As briefed above, adaptive authentication is a machine learning based security solution which is driven by certain parameters to benefit users with easy, engaging simplified and yet stronger security authentication.

Adaptive authentication is not a separate solution or application rather it’s an integrated part of 2FA or any other Multi-factor authentication solution. During adaptive authentication, different parameters and user-attributes are being taken into consideration to identify the risk and the credibility of the login. Positive results during adaptive authentication grants, direct access to users without letting them undergo through token based second-factor authentication. However, if the login found to be suspicious based on multiple risk-identifying factors, then that login is further subjected to second-factor authentication where the user needs to present hardware or software token.

What are the parameters considered during adaptive authentication?

Below given, are some of the most used parameters and user-attributes to authenticate the veracity of user’s login. Based on the following factors, a user may be granted direct access or may be subjected to 2nd-factor authentication check.

  • User-Behaviour
  • Login Time
  • Device and other software and hardware resources used for access.
  • IP address of login.
  • Geographical location of user’s login

The above-mentioned attributes with the aid of machine learning tools and algorithms are being used to evaluate and assess the credibility of the login. Some more and unique parameters and attributes could also be added to the list to ensure a stronger authentication check

Why Adaptive authentication is getting popular?

The primary and maybe the single-most reason behind adaptive authentication hype is the ease of authentication that user is finding pretty useful and engaging. Although second-factor authentication proven to deliver stronger security, at the same time, users were finding authentication procedure very tiresome and frustrating as they need to authenticate themselves repeatedly in the second-factor authentication check, each time they want to login throughout the day.

Adaptive authentication is a very useful mechanism that lets genuine and authorized user to gain direct access without getting introduced to 2nd-factor authentication window, unless and until he/she tries to log in from some unusual location, IP address, using unconventional software or hardware devices or in odd timings.

Thus, Adaptive authentication not only ensures productive machine learning based security check, but also increases and maintain user-interest, and thereby delivers higher satisfaction rate.

At present, very few of the network security solution providers are delivering adaptive authentication features with their 2FA or MFA solution like REVE Secure. To ensure high-level of security, but not at the cost of their user’s interest and experience, organizations need & must implement machine learning based adaptive authentication.