Behavioral biometrics is the field of study related to the measure of uniquely identifying and measurable patterns in human activities. The term contrasts with physical biometrics, which involves innate human characteristics such as fingerprints or iris patterns.
Behavioral biometric verification methods include keystroke dynamics, gait analysis, voice ID, mouse use characteristics, signature analysis and cognitive biometrics. Behavioral biometrics are used for secure authentication in financial institutions, businesses, government facilities and retail point of sale (POS), as well as an increasing number of other environments.
To increase security and prevent use of biometric credentials for identity theft, biometric data is typically encrypted during gathering and verification. After biometric data is gathered, a software application picks out specific points of data as match points. The match points in the database are processed using an algorithm that translates that information into a numeric value. The database value is compared with the biometric input the end user has entered and authentication is either approved or denied.
Unlike many types of physical biometrics, behavioral biometrics can often be gathered with existing hardware, needing only software for analysis. That capacity makes behavioral biometrics simpler and less costly to implement.