Behavioral biometrics

Behavioral Biometrics refers to the study of measuring analyzing patterns in human activity to identify individuals with an exceedingly high degree of accuracy. Patterns include keystroke, speech, gait, signature and cognition, helping capture an array of human interactions between a device and an application. By measuring how consumers hold phones, swipe screens, use keyboard or gestural shortcuts, software algorithms build a unique user profile, which is then used to confirm an individual’s identity. Hence, behavioral biometrics emphasized on how an activity is performed to test it authenticity. For example, despite a user’s password being entered correctly, behavioral biometrics tests the typing speed or transitions between keys.

Behavioral biometrics is currently used on several platforms including online banking, e-commerce, and high-security authentication. It helps create an additional and continuous layer of identity assurance and security. As greater number of applications progress to the online space, there is higher consumer demand for the ability of functions in their digital worlds to match their physical worlds, resulting in growing popularity for behavioral biometrics.

History

The initial use of behavioral biometrics to measure patterns in human activity dates back to the 1860s with the invention of the telegraph. In World War II, allied forces would use the telegraph to verify legitimacy of messaged received by testing the method of transmission. In the 1960s, the advent of computers allowed for the first model of acoustic speech production followed by the earliest signature recognition system. Today, behavioral biometrics extends beyond signature, voice and speech, as modern systems are able to identify an array of data and end-point interactions.