Why A Risk-Based Approach To Authentication Makes Sense

With adaptive or risk-based authentication, organizations can leverage machine learning to build risk profiles based on employee information to strengthen their cybersecurity measures. A variety of inputs such as location, network reputation and device fingerprint make up the composite score to determine the risk potential of any sign-in attempt. Risk-based authentication then scores each login action based on established user profiles and adjusts the number of required authentication factors based on the level of suspicion. The higher the risk score, the more additional layers of authentication may be required, such as a one-time password to grant user access.