Page 101 - Cyber Defense eMagazine for September 2020

“Biometric authentication is a security process that relies on the unique biological characteristics

of an individual to verify that he is who he says he is. Biometric authentication systems compare a
biometric data capture to stored, confirmed authentic data in a database.” (Haughn, 2020)

There are several different types of biometric authentication, and new technologies are being
developed every day. Facial scanning and fingerprint scanning are common and found on most smart

phones and personal devices. There are many other types, however, such as retina scanning, iris
recognition, and palm vein scanning and hand geometrics. Artificial intelligence has allowed new
methods to be developed, such as keystroke rhythms. “Identifying or authenticating people based on

how they type is not a new idea, but thanks to advances in artificial intelligence it can now be done with
a very high level of accuracy, making it a viable replacement for other forms of biometrics.” (Constatin,

2017)

“Unlike the Personal Identification Numbers (PIN) and passwords, biometric data is nearly

impossible to guess and is unique to a single person.” (Thompson, 2018) Although it may seem that
biometrics are foolproof, they are not. “No one method is without limitation and there is still a way to go
until biometric authentication methods become affordable and trusted enough for widespread adoption.”

(Thompson, 2018)

Unless you write down your PIN number or password, it is statistically improbable that it would be

guesses by a human. Passwords are encrypted with a one-way hash. Fingerprints, unlike passwords,
are left on everything you touch. The issue is further compounded by the massive stockpiles of

fingerprints in the hands of US authorities, with more than 31 million in a Department of Homeland
Security biometrics database as of 2014 and more than 34 million belonging to civilians also in an FBI
database as of 2010. (Sputnik International, 2018) History has shown that our government networks are

susceptible to compromise. Even more interesting, machine learning has made it easy for researchers
to develop “a technique to create so-called DeepMasterPrints: fake fingerprints designed to trick

scanners.” (Newman, 2018)

Iris scans are considered highly reliable and are extremely accurate, however the cost of

equipment required to get the detail necessary to validate the scan is very high. “Large companies,
agencies or Governments can afford that price, but the general public can’t afford to pay that price. Some
say that it costs five times higher than fingerprint scanning which is more readily available to the general

Cyber Defense eMagazine – September 2020 Edition 101
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