Multi-factor authentication (MFA) is a multi-step account login process that requires users to enter more information than just a password. For example, along with the password, users might be asked to enter a code sent to their email, answer a secret question, or scan a fingerprint. A second form of authentication can help prevent unauthorized account access if a system password has been compromised.
Digital security is critical in today's world because both businesses and users store sensitive information online. Everyone interacts with applications, services, and data that are stored on the internet using online accounts. A breach, or misuse, of this online information could have serious real-world consequences, such as financial theft, business disruption, and loss of privacy.
While passwords protect digital assets, they are simply not enough. Expert cybercriminals try to actively find passwords. By discovering one password, access can potentially be gained to multiple accounts for which you might have reused the password. Multi-factor authentication acts as an additional layer of security to prevent unauthorized users from accessing these accounts, even when the password has been stolen. Businesses use MFA to validate user identities and provide quick and convenient access to authorized users.
Reduces security risk: Multi-factor authentication minimizes risks due to human error, misplaced passwords, and lost devices.
Enables digital initiatives: Organizations can undertake digital initiatives with confidence. Businesses use MFA to help protect organizational and user data so that they can carry out online interactions and transactions securely.
Improves security response: Companies can configure an MFA system to actively send an alert whenever it detects suspicious login attempts. This helps both companies and individuals to respond faster to cyberattacks, minimizing any potential damage.
Multi-factor authentication works by requesting multiple forms of ID from the user at the time of account registration. The system stores this ID and user information to verify the user for the next login. The login is a multi-step process that verifies the other ID information along with the password.
We describe the steps in the MFA process below:
Registration: A user creates the account with username and password. They then link other items, such as a cell phone device or physical hardware fob, to their account. The item might also be virtual, such as an email address, mobile number, or authenticator app code. All these items help to uniquely identify the user and should not be shared with others.
Authentication: When a user with MFA-enabled logs into a website, they are prompted for their username and password (the first factor–what they know), and an authentication response from their MFA device (the second factor–what they have).
Reaction: The user completes the authentication process by verifying the other items. For example, they might enter the code they have received or press a button on the hardware device. The user gets access to the system only when all the other information is verified.
Adaptive multi-factor authentication, or adaptive MFA, uses business rules and information about the user to determine which authentication factors it should apply. Businesses use adaptive authentication to balance security requirements with the user experience.
For example, adaptive authentication solutions can increase or decrease user authentication steps dynamically by using contextual user information such as:
Number of failed login attempts
Geographical location of the user
Geo-velocity or the physical distance between consecutive login attempts
Device being used for login
Day and time of login attempt
Operating system
Source IP address
User role
AI-driven multi-factor authentication solutions use artificial intelligence (AI) and machine learning (ML) to analyze trends and identify suspicious activity in system access. These solutions can monitor user activity over time to identify patterns, establish baseline user profiles, and detect unusual behavior, such as:
Login attempts at unusual hours
Login attempts from unusual locations
Login attempts from unknown devices
ML algorithms assign risk scores to suspicious events and adjust multiple authentication factors in real time based on business policies. For example, if the behavior is classified as low-risk, the user can sign in with just a username and password. On the other hand, the user must enter an SMS code for medium-risk behavior, and if the behavior is high-risk, the user is denied access altogether.
Remote access to employees:
A company wants to give remote resource access to its employees. It can set up MFA requiring login, a hardware fob, and a fingerprint scan on company-issued laptops that the employees take home. Based on the employee's IP address, the company can set rules that the employee needs to use two-factor authentication when working from home. However, the company may require three-factor authentication when the employee is working on any other Wi-Fi network.
System access to on-site employees only:
A hospital wants to give access to its health applications and patient data to all its employees. The hospital gives the employees a proximity badge to access these applications while they are at work. At the start of each shift, the employee has to log in and tap the badge to a central system. During the shift, they can access all resources with a single tap of the badge, without more login requirements. At the end of the shift, the single tap access rights end. This minimizes the risk of unauthorized access due to lost badges.
MFA authentication methods are based on something you know, something you have, and/or something you are. We describe some common authentication factors below:
Knowledge factor: In this method, users have to prove their identity by revealing information no one else knows, such as secret questions or pin codes.
Possession factor: In this method, users identify themselves by something they uniquely own, such as physical devices like mobile phones or security tokens.
Inherence factor: Inherence methods use biometric information that is inherent to the user, such as fingerprint scans, retina scans, or voice recognition.
All businesses should set up enterprise-wide policies to restrict access and secure digital resources. The following are some of the best practices in access management:
Create user roles: Fine-tune access control policies by grouping users into roles.
Create strong password policies: Implement rules to create strong passwords, even with MFA.
Rotate security credentials: Ask users to change passwords regularly.
Follow least privilege policy: Start new users at the lowest level of privilege and access rights in your system.