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    The Significance of Adaptive Multi-Factor Authentication in Ensuring Data Security

    According to IBM’s Cost of a Data Breach Report 2020, a data breach’s global average cost is $3.86 million. The same for the United States is $8.64 million. Now that we know how costly it is to get hacked, it goes without saying that relying on simple username and password authentication in today’s digital environment is not enough to secure sensitive business data and systems from the increasingly sophisticated number of cyber-attacks.

    Multi-Factor Authentication (MFA): The Need

    Multi-factor authentication (MFA) helps companies secure access to their applications and systems. With MFA, users must have two or more authentication factors when accessing apps, networks, or services. MFA implementations make use of a combination of the following variables:

    • Something you are aware of, such as a username, password, PIN, or a security question answer;
    • Something you have, such as a tablet, a one-time passcode, or smart card;
    • Something you are, like biometrics such as your fingerprint, retina scans, or voice recognition, etc.

    But if MFA is applied the wrong way, if you are continuously prompted to a second factor every step of the way, it can become a “in your face” authentication experience. Implementing adaptive MFA is the next logical advancement to make access to systems and applications more “user-friendly” without compromising security.

    Adaptive Multi-Factor Authentication

    Adaptive MFA is a way to configure and deploy multi-factor authentication in such a way that the Identity Provider (IdP) selects the correct multiple authentication factors based on the risk profile and behavior of a user as part of an ongoing process, instead of just applying risk assessment and elevation once during the authentication process. Well, it’s all about adapting the form of authentication to the event.

    Depending on the capabilities of the IdP, there are three ways adaptive authentication can be configured:

    1. Static policies that identify risk levels may be set for various variables, such as user position, the value of resources, location, time of day, or day of the week.

    2. Based on their tendencies over time, the device may learn the usual behaviors of users. Similar to the behavioral correlation is this learned type of adaptive authentication.

    3. A combination of both static as well as dynamic policies.

    Many MFA mechanisms, such as mobile push alerts, derived credentials, SMS verification, and more, can support a sophisticated adaptive authentication IdP system.

    Adaptive authentication should adapt to the risk level, offering the required level of authentication for the defined level of risk, regardless of how you might identify your corporate risk levels. It avoids making low-risk activities inappropriately burdensome or high-risk operations too easy to hack, unlike the standard, one-size-fits-all authentication approach.

    The following can be looked at with adaptive authentication:

    Device Profile: What system does the request come from? Is this a machine that I’ve seen before? Is this a computer that’s provided by the company?

    Location Awareness: Where does this request come from? Is this a “risky” range of IP address, is this a “risky” country? This is not the default location that this user is logging in from.

    User behavior: Why is the user accessing such servers/applications/data? Never before has he done that.

    Conclusion

    It makes it easier for IT and the end-user to use adaptive MFA to access applications and services, resulting in a happier workforce and protecting the sensitive business data.

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