Biometric authentication refers to a cybersecurity process that verifies a user’s identity using their unique biological traits such as fingerprints, voices, retinas, and facial features. Biometric authentication systems store this information in order to verify a user’s identity when that user accesses their account. This type of authentication is usually more secure than traditional forms of multi-factor authentication.
Biometric authentication refers to a cybersecurity process that verifies a user’s identity using their unique biological traits such as fingerprints, voices, retinas, and facial features. Biometric authentication systems store this information in order to verify a user’s identity when that user accesses their account. This type of authentication is usually more secure than traditional forms of multi-factor authentication.
Types of Authentication Methods
The following are a few common authentication methods used for network security designed to beat cybercriminals and some of the biometric authentication technologies below are ones that you might use daily.
Facial recognition: These systems use a person’s unique facial features to identify them. It’s used in a variety of places such as smartphones, credit card payments, and law enforcement.
Fingerprint Recognition: Fingerprint authentication uses a person’s unique fingerprint to verify their identity, using a device like a FIDO2 Authentication Token. It can be used to secure everything from mobile devices to automobiles, even buildings, making it the most widespread biometric authentication technology.
Eye Recognition: Eye recognition uses the unique pattern of someone’s iris or retina to identify them. Because this type of biometric authentication is harder to implement, it’s less common than the other types of biometric authentication options. An iris scan requires an infrared light source, a camera that can see IR, and minimal light pollution in order to ensure accuracy. Although it poses its challenges, it is one of the most accurate biometric authentication systems available when those conditions are met. Eye recognition is generally used in situations where security is most critical such as nuclear research facilities, etc.
Voice Recognition: Voice recognition uses the tone, pitch, and frequencies that are unique to an individual to authenticate them. This is the most commonly used biometric to verify users when they contact a call center for customer service support (for example, online banking)
Retina/Iris Recognition: Retina or also known as iris recognition, uses the pattern of someone’s iris or retina to identify them. This type of biometric authentication is less common as it is harder to implement. It requires the implementation of an infrared light source, a camera that can see IR, and minimal light pollution to ensure accuracy. However, it happens to be one of the most accurate biometric authentication methods when those conditions are met. So it’s typically used in situations where security is most critical (nuclear research facilities, for instance).
Gait Recognition: Gain recognition authenticates using the way someone walks to identify them. Each person walks a little differently, so the way a person puts one foot in front of the other is an effective way to verify their identity. As of now, it’s not a common form of authentication but it’s expected to become more common as future forms of authentication become more popular.
Vein Recognition: Vein recognition uses the pattern of blood vessels in a person’s hand or finger to identify them. This type of biometric authentication uses infrared light to map the veins under the skin in your hands or fingers. Vein recognition is extremely accurate, more than retina/iris recognition.
First, we need to understand what a unimodal biometric authentication system is. Essentially it’s a system that verifies only one distinct characteristic, e.g face, retina. However, this system is very susceptible to spoofing.
This is where multimodal biometric authentication comes into play. It’s an approach in which various biometrics are checked during identity verification. This makes it harder for a malicious hacker to spoof.
An example of multimodal authentication: A hacker may be able to find a person’s photo on the internet, which they then use to successfully trick a facial recognition system into thinking it’s the actual user. If the system just had the one authentication, then the users accounts would be hacked. However, if the system requires the user to provide additional authentication such as a video of the person saying their password, then the hacker is very unlikely to find it.
By combining physical and behavioral authentication, you can enhance your security posture. Even if a malicious actor manages to spoof a fingerprint, the system can detect change in behavior and deny entry. E.g., their speed of interaction with the system may be slower than the real user, or they are using keyboard shortcuts that the real user never used.
Benefits
Identity insurance: Biometric identification provides the answers to “something a person has and is” and helps verify identity. Biometric authentication ensures increased levels of assurance to end-users. Its sophisticated software lets providers know that a person is who they claim to be through a tangible, real-world trait. Even if a cyber attacker knew of a user’s password or the answer to their security question, there’s no way they’d be able to duplicate a fingerprint or iris scan.
Ease of Use: While biometric authentication is more on the technical side in regards to its internal process, it’s generally easy and quick from a user’s point of view. By using either a fingerprint scanner to unlock an account or facial recognition, you’re cutting down the amount of times you have to log in using a long password that has multiple special characters in it that you will likely end up forgetting. Apple does a great job with biometric authentication, both fingerprint and facial, in their devices.
Fraud Detection: Biometrics are almost nearly impossible to replicate. They’re hard to replicate and steal, and only have about 1 in 64 billion chances that your fingerprint will match up exactly with someone else’s. It’s highly unlikely that a hacker will be able to access anything that’s secured with biometrics.
Risks
Being Hackable: Biometrics can still be hacked. Businesses and governments that collect and store users’ personal data are under constant threat from hackers. If however, they are a victim of a data breach, biometric data is irreplaceable, and organizations need to treat users’ biometrics with care and caution.
Partial Matches: Most common biometric authentication methods rely on partial information to authenticate a user’s identity. For example, during the enrollment process of registering your fingerprint, it will take data from your entire print and convert it into data. During future authentication however, it will only take partial fingerprint data to verify your identity so it’s faster and quicker.
Fail to Recognize a Valid User: When you register for facial recognition, you are registering a specific angle, and expression to your face. However, because the system only has the data from the enrollment process, anytime a user wears glasses, makeup, or even smiling, the facial recognition has a hard time recognizing the user, which could make the login process difficult.
Bias: Facial recognition systems may not recognize persons of color or non-cisgender people as accurately. Many biometric systems have been trained primarily using white or white male photos. This incorporates in them an inherent bias that results in difficulty recognizing women and people of color. Poor implementation of technology or deliberate misuse can result in discrimination and exclusion. Without a proven identity proofing solution, cross-demographic performance can be unreliable.
Fears of Sharing Biometric Data: Is it acceptable for companies to sell or provide their biometric data to others, such as law enforcement, immigration enforcement, or repressive foreign governments. These privacy concerns have caused many US states to enact biometric information privacy laws. When biometrics are converted into data and stored, particularly in places or countries that have large surveillance measures, a user runs the risk of leaving a permanent digital record that can be potentially tracked by nefarious actors.
Data Storage: Wherever biometric data is stored, it must be stored securely. Biometric data cannot be reset like a password. If biometric data is hacked, then there’s really nothing a user can do as they cannot change their fingerprint or iris.
As we know, biometrics add an additional barrier to other security measures, enabling multi-factor authentication. Biometrics are generally bound to the mobile device or laptop as its use requires the user’s physical presence to authenticate. Biometric authentication is a powerful type of authentication because unlike passwords, they are extremely difficult to recreate.
Passwords on the other hand, can be easily hackable through multiple methods. The most common is phishing attacks where hackers masquerade as a customer service rep or send an email to a user asking for their login credentials. With biometric authentication, you cannot send an accurate authentication method without being physically present or registered to that device.
Biometric authentication is the stronger method as it is unique to the user’s facial and fingerprint identity. There’s no way for it to be replicated making spoofing attacks a lot less common.
Myth – Biometric technology is an invasion of privacy: Biometric authentication solutions generally require the user to consent to enrolling in biometric authentication. In terms of storage, a photographic image of a user’s face is not stored in a database, only a mathematical model of the face is stored which is essentially useless to a hacker.
Myth – Biometric identification can be fooled by static images and photographs: Modern biometric authentication solutions are more advanced than older models. Modern biometric solutions can ask a user to further authenticate themselves through turning their head, blinking, or even smiling. This eliminates the chances of static images being approved through biometric authentication.
Myth – Biometric models expire as the user ages or features change: With modern biometric solutions, this isn’t a worry as the user is typically authenticated on a regular basis. This means that the small changes in appearance will not be large or significant enough to invalidate the match. Instead, the mathematical data just updates as it recognizes these changes.
Myth – Biometric identification is only applicable if the user is already known: Part of biometric authentication is behavioural biometric. How a user holds their phone, swipe, or type on their keyboard, can be used to develop a profile to authenticate a user or determine relative risk of a transaction.
There are many different use cases for biometric authentication that vary across a wide range of industries.
Healthcare
Hospitals mainly use biometric authentication to accurately track patients and prevent any mix-ups. Clinics and doctors offices tend to implement biometric authentication to keep their patients’ information secure. By using biometric authentication, hospitals and clinics can store and access patients’ medical history at any time.
Travel
An electronic passport contains a microchip that stores the same biometric information as a conventional passport. The chip stores a digital image of the passport holder’s photo which is linked to their name and other information that identifies them. The e-passport is issued electronically by a country-issuing authority, which checks the identity of the applicant through fingerprints or other biometric information and confirms the data in the chip with the information provided by the applicant before issuing the passport.
Law Enforcement
Law enforcement uses different kinds of biometric data for identification purposes. State and federal agencies use fingerprints, facial features, iris patterns, voice samples, and DNA. This makes it quicker and easier for them to access confidential information. Normally law enforcement uses a trained human examiner to compare a fingerprint image to the prints on file. Today, AFIS (Automated Fingerprint Identification System) can match a fingerprint against a database of millions of prints in a matter of minutes.