By 2020, 90% of organizations will make use of some form of biometric system to verify and monitor workplace activity, IT professional network Spiceworks predicts.
While most biometric authentication systems use fingerprint scanning, iris scanning, or facial recognition to beef up workforce security, other safer and more novel tools are emerging – tracking unique identifiers HR leaders never thought were measurable.
What is biometric data, anyway?
Biometric data refers to computer data taken from measuring or calculating a person’s attributes or actions. Most forms rely on a person’s physiological traits, such as their fingerprints or patterns in the iris – but others also read into a person’s behavior.
Behavioral biometrics can help employers monitor the workforce without the same risk posed by other more sensitive biometric data such as a person’s face. These are less risky alternatives:
1. Keystroke dynamics
When it comes to frictionless authentication, organizations use keystroke dynamics to identify users and detect unauthorized access covertly. This automated process “remembers” legitimate users based on the pattern, speed, and rhythm of their typing. Advocates of this biometric tool believe each person has a signature method of locating and pressing down on keys. Unauthorized use will be gauged using the known keystroke identity of official users.
2. Voice biometrics
Because of the rise of natural language processing, the use of voice biometrics to ID individuals could not be far behind. Voice biometrics, however, is different in that it focuses on how a person says something, not the words they say.
The technique captures a person’s “voiceprint” based on the sound and rhythm of their voice or pattern of their speech. But even so, this tool is not entirely foolproof. HSBC, which deploys a voice recognition system, had reportedly been duped by a BBC journalist in the past.
Security experts, however, recommend using voice recognition as part of multifactor authentication – not as a standalone security tool.
3. Signature recognition
Similar to keystroke dynamics, signature recognition identifies a user by the structure of their signature (static method) or by the hand stroke of the user while signing their name or scribbling a security phrase (dynamic method).
Security experts often prefer dynamic signature recognition to the static one. The dynamic method is purportedly difficult to manipulate with fake signatures because it takes into account other factors such as the direction or pressure of handwriting, which forgers cannot easily replicate.