![\"onelogin-adapt-auth-header\"](\"https:\/\/solutionsreview.com\/identity-management\/files\/2017\/04\/onelogin-adapt-auth-header.jpg\")
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By now, we should all be aware that passwords are generally insufficient to secure anything worth securing. Enterprise security teams have known for years, and the generally accepted best practice has been to implement Multi-Factor Authentication (MFA) solutions.<\/p>\n
MFA solutions take traditional, knowledge-based Auth factors, such as passwords and up the security by adding additional factors such as possession factors (something you have) and inherence factors (something you are) to the authentication process.\u00a0This could mean a hard token, or a biometric, such as a fingerprint.<\/p>\n
But as any InfoSec pro knows, securing corporate environments is a careful balancing act between security and user convenience. Now, OneLogin is looking to make finding that balance a little easier with its newest updated, adaptive multi-factor authentication.\u00a0<\/em><\/p>\n OneLogin\u2019s adaptive authentication tracks a user\u2019s movement across networks, devices, browsers, and geographies over time, and uses machine learning to build a user profile against which new login attempts and password resets can be scored by risk. Some of the factors included in the scoring are IP reputation, device fingerprinting and geographic location. At the time of authentication these factors are scored against the user\u2019s profile and the number of required authentication factors are adjusted accordingly.<\/p>\n \n The number of authentication factors required by a user in a given situation is\u00a0based on risk. When risk is high, OneLogin prompts the user to authenticate with multiple factors, which risk is low, it doesn’t. For example, if a user who commonly logs into work in Boston logs into the network from a device in Russia, multiple auth factors would be required.<\/p>\n