Context Matters: Using Machine Learning for Adaptive Authentication

Imagine an individual attempting to impersonate an employee and walking into your office to steal intellectual property. As they approach the front desk, they’re visibly nervous, and even more conspicuously, wearing strangely formal clothes for an office populated by jean-wearing millennials. Your security team realizes immediately that something is amiss and stops the intruder in their tracks before any harm can occur.

By analyzing context—in this case, out of place clothes and visible discomfort—to inform decision-making, our imaginary security team provides a model for more effective cybersecurity. And though these visual clues don’t transfer to the digital realm, the situation underscores a critical concept in adaptive authentication—using context to set application and data access policies or kickstart security procedures.