Why do we need adaptive 2FA (two factor authentication)?

Two factor authentication (2FA) has helped everyone connected to the internet in keeping their accounts, data, services… safe from the attackers. It’s a highly robust security layer, which is extremely hard to crack. The question is, if it is that safe to use 2FA, why do we need adaptive 2FA. The answer is simple, better security and accessibility. Let’s justify the answer over this discourse.

Adaptive 2FA

Adaptive authentication is a new security feature that uses machine learning to verify the authenticity of a login before prompting the user for two factor authentication. Let’s break this up. First, from user’s point of view, adaptive authentication is just an add-on to their 2FA authentication solution. The user will not interact with adaptive authentication security layer directly. Second, it uses machine learning. Machine learning uses algorithms to learn patterns in data and make predictions based on that data. This gives machines (processors) the ability to decide. Third, the veracity of the login attempt is confirmed on the service provider’s end. This process checks from various patterns learned from the account owner, if the login attempt is valid and secure.

New authentication factors lead traditional methods towards deprecation.

Choosing the authentication factors

Two factor authentication adds complexity to the login process. Each additional authentication factor added to the login process (3FA, multi factor authentication, etc.) incorporates inefficacy. Adaptive authentication strengthens the security of a user’s account without adding any complexities to the login process. Utmost attention is paid while choosing the authentication factors. Too many authentication factors may ultimately slow down the authentication process and make it cumbersome. A balance is maintained between security and usability by adding only the most significant factors, like login time, device used for access, IP at which the login originated, geolocation, and security of the communication channel. A user’s behaviour is recorded and analysed based on these authentication factors to create the user’s risk profile. The machine learning algorithms adapt to the user’s risk profile and tendencies to develop an effective mechanism for verifying the veracity of the login attempt.

Effortless security for users

Identity management gets easier with the use of adaptive authentication, both for the end-user and enterprise. The user will not have to be bothered with different authentication layers. Instead, the entire process of authentication will be swift and easy. Enterprises will not have to dedicate security personnel to verify the reliability of a login attempt, saving both resources and time. Also, machines are fast. The entire adaptive 2FA process executes in the background with negligible time delay. In most cases, the user will not be even aware of the verification that has taken place.

Efficacy and Usability

Adaptive authentication can verify several factors associated with the login attempt, before the user gets to 2FA. Not only this, adaptive authentication can even allow a user to bypass 2FA based on the veracity of the login attempt. e.g. When not in office, Max always uses his personal mobile device to login to his work account. Before implementation of adaptive authentication, each time Max tried to log in, he was subjected to two factor authentication. But few days after adaptive authentication was implemented on his company’s server, Max stopped getting 2FA requests and could login through user ID and password alone. Through adaptive authentication the server knows that it is Max who is trying to access his account from the same mobile device he’s used in the past. Isn’t it easier? And it’s just through a single factor. The adaptive authentication algorithms use a number of factors and complex statistics to build user profiles.

Dynamic and (per the name) Adaptive

The processes and algorithms involved in adaptive 2FA are dynamic. They keep building and updating the user risk profile. At each attempt, along with verifying the authenticity of the login the attempt, the login pattern is analysed and recorded. The entire process of learning, analysing, and authenticating is dynamic in approach and adaptive to situation. The algorithms learn from and adapt to the login conditions. For high risk profiles or questionable login circumstances, more authentication factors may be incorporated.

Adaptive authentication can even identify malicious users and malicious bots trying to gain access to a user’s account through hacked or stolen passwords and deny them authentication altogether. Any malicious user will not even get to the two factor authentication.

Adaptive authentication is a hidden layer of security that verifies the veracity of the login attempt through machine learning. It is simple, secure, efficient, and dynamic of all things. It uses large range of inputs and factors to build a user’s risk profile to facilitate authentication. It reinforces security of an account without adding any extra verification steps for the user.

Shift to Adaptive Authentication

You must have heard the terms two-factor authentication and multi-factor authentication, used for improving security and protecting web logins and accounts from malicious attack and data breaches. However, organizations are seeking better solutions to ensure higher user-satisfaction rate along with stronger security for their assets. Adaptive authentication is an advanced and excellent methodology for authenticating users based on machine-learning and data analytics to deliver great 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 integral part of 2FA or any other Multi-factor authentication solution. During adaptive authentication, different parameters and user-attributes are taken into consideration to identify the risk and the credibility of the login attempt. Positive results during adaptive authentication grant direct access to users without letting them undergo token based second-factor authentication. However, if the login attempt is found to be suspicious, based on multiple risk-identifying factors, then it is further subjected to second-factor authentication where the user needs to present hardware or software token, or discredited entirely.

What parameters are considered during adaptive authentication?

Given below are some of the most used parameters and user-attributes to authenticate the veracity of a 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/hardware resources being used for access
  • IP address of the login
  • Geographical location of user’s login

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

Why is Adaptive authentication getting popular?

The primary and maybe the single-most reason behind the hype of adaptive authentication is the ease of authentication, which the users are finding to be pretty useful and engaging. Although second-factor authentication has been proven to deliver stronger security, some users find the authentication procedure very tiresome and frustrating because of the second-factor authentication that takes place each time they try to log in.

Adaptive authentication is a very useful mechanism that lets genuine and authorized user gain direct access to their account without performing the 2nd-factor authentication unless the user tries to log in from some unusual location, IP address, using unconventional software, or hardware devices in odd timings.

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

At present, very few network security solution providers, e.g.  REVE Secure, are delivering adaptive authentication features with their 2FA or MFA solution to ensure a high level of security, but not at the cost of the user’s interest and experience.