Biometric Devices – Complete Guide on Technology

Though biometric technology is in its developing phase, its science is not new. The study of manual fingerprint recognition extends back to the end of the nineteenth century, while iris recognition dates back to 1936. Breakthroughs, notably in biometric technology in the security and surveillance sectors, occurred in the second half of the 1980s. Today biometric technology is being increasingly recognized, particularly after the coronavirus pandemic.

Table of Contents

What Are Biometric Devices: Definition of the Term

Different Types of Biometric Devices

Optical Sensors

Capacitive Scanners

Ultrasonic Sensors

Thermal Line Sensors

Types of Biometric Devices Also Include

Biometric Authentication Devices

Biometric Identification Devices

Biometric Security Devices and Their Use

How Do Biometric Devices Work?

Biometric Measurements

Physiological Identifiers

DNA Recognition

Ear Recognition

Iris Scanning

Retina Recognition

Face Recognition

Fingerprinting

Finger Geometry Recognition

Hand Geometry

Odour Recognition

Vein Recognition

Behavioral identifiers

Gait Recognition

Keystroke Recognition

Voice Biometrics

Signature Recognition

History of Biometrics

Advances in Biometrics Over the Years

Who Uses Biometric Devices?

Civil Security

Military Needs

Border & Migration Control

Civil Identification

Healthcare

Access Control

Commercial Applications

Trends and Future of Biometrics

Image Compression for Face and Fingerprint Recognition Systems

Biometric Liveness Detection Technique

Posterior Authentication

Pixel Stack to Record Multi-Biometrics

Is Biometrics Reliable: Security Aspects of Biometric Devices

Biometrics Market and Industry Report

Trends in Biometrics Market

How Accurate Is Biometrics in 2021?

What Are the Pros and Cons of Biometric Devices

Pros of Biometric Devices

Cons of Biometric Devices

What Is a Cross-Context Attack in Biometric Devices

Biometric Cards and Tokens

Documents

Conclusion

FAQ

What Is CER in Biometric Devices?

How Do Biometric Devices Help Improve Security?

How Popular Are Biometric Devices?

What Are Biometric Devices Used For?

What Are Biometric Devices: Definition of the Term

Biometric devices are used for security identification and authentication. These devices can recognize a user and then correctly prove whether the identified user holds the identity they claim to have.

Biometric security systems use automated techniques, in which human intervention is reduced to the minimum to recognize and then confirm an individual’s identity based on distinctive physiological or behavioral features, such as fingerprints, face pictures, iris recognition, and voice recognition.

Different Types of Biometric Devices

The different types of biometric devices have varying ranges of characteristics, benefits, and limitations. While selecting a biometric recognition system, prices are also a crucial factor. In the case of multimodal, the cost of biometric devices may increase significantly. Therefore, it is essential to balance all the characteristics, benefits, and limitations by conducting thorough research before opting for multimodal biometric recognition.

The most prevalent format is fingerprinting, mainly because it is affordable, easily implemented, and user-friendly. These features allow them to have the highest penetration when used in authentication and security systems in smartphones and other portable biometric devices. For scanning a design, biometric input devices like fingerprint scanners employ sensors with several ways to fingerprint, read, and generate images.

Below are the commonly used sensors in fingerprint scanners.

Optical Sensors

Optical sensors work by focusing light on your fingerprint to capture a digital image. This light-sensitive microchip turns the digital image into 0’s and 1’s by examining the fingerprint’s ribs and valleys and producing your customized code. It is the most commonly used fingerprint sensor and is available at affordable rates. However, these sensors also have a few disadvantages, such as duplication of the digital image, poor quality due to unclean fingers, and easier to be tricked.

Capacitive Scanners

Capacitive fingerprint scanners are most commonly found on smartphones. It measures your fingerprint by leveraging human conductivity, producing an electrostatic field, and generates a digital picture based on the electrostatic field. This process is achieved through arrays of capacitor circuits.

Using the ridges of your fingerprint, which are put over the conductive plates, the scanner modifies the charge stored in the capacitor while the valleys remain intact. These variations are tracked by an operational amplifier integrator circuit, which is subsequently collected by an analog-to-digital converter and evaluated. Costlier than optical sensors, capacitive scanners cannot be easily tricked.

Ultrasonic Sensors

Ultrasonic sensors calculate the distance to your fingerprint via ultrasonic sound waves. This distance is measured using a transducer that sends and receives pulses (ultrasonic), which further provide details, such as time lapses, on the closeness of the fingerprint. Once the sound waves have been measured, the fingerprint’s image is created. Unlike capacitive scanners, the quality of output by ultrasonic sensors is not affected by unclean fingers.

Thermal Line Sensors

Thermal line sensors use temperature alterations in the fingerprint’s ridges and valleys to produce a fingerprint pattern output. These sensors are small in size and are arranged in an array, and the fingerprint is made to rotate over it.

Types of Biometric Devices Also Include

Based on their functionality, biometric devices are classified into the followed types:

Biometric Authentication Devices

In biometric authentication, an individual’s characteristics data is compared with the same individual’s biometric template. The aim is to confirm whether the individuals hold a resemblance to their claimed identity.

Biometric authentication systems compare physical or behavioral characteristics to data in a database that has been identified. Authentication is established when both sets of data align. Biometric authentication is often used to control access to buildings, rooms, and computers.

• The first step involves storing the reference model.
• This stored data is matched with the biometric data for resemblance.

Since the goal of biometric authentication is to confirm the identity of the individual, the question asked is, “Can you confirm you are XYZ?”

Biometric Identification Devices

In biometric identification, an individual’s identity is determined. In most cases, biometric identification refers to a scenario in which an organization needs to identify a person. The organization takes a biometric from that person and compares it to a biometrics database in an attempt to accurately identify the person.

• The goal is to obtain a piece of biometric data from this individual. It might be a photograph of their face, a recording of their voice, or a fingerprint picture.
• Once the data has been collected, it is matched with biometric data of other individuals within the database.

Since the goal of biometric identification is to identify the identity of the individual, the question asked is, “Who are you?”

Biometric Security Devices and Their Use

The different types of biometric security devices entail using biometric security software to verify individuals by considering their biological or behavioral features. Owing to its low cost, fingerprint recognition is the most common technology used in these devices.

Multispectral fingerprint sensors, though costlier, are often a better alternative than optical fingerprint sensors when it comes to 2D fingerprint sensors. Facial images, irises, palm veins, and finger veins are other markers utilized. In the context of high security, iris recognition, followed by palm recognition, is considered the best option.

How Do Biometric Devices Work?

A sensor, a computer, and software are three key components of biometric devices. All biometric systems work through the same three stages:

1. Enrolment: When you use a biometric system for the first time, it will collect some of your details, such as the name you provide or your identification number. Next, the system will record an image or a particular characteristic.
2. Storage: Rather than saving the entire image or recording, the recorded characteristic is evaluated and converted into a graph or a line of code.
3. Comparison: The second time you interact with the biometric system, it will compare the characteristic you offer with its stored data. There will be either of the two outcomes – the biometric system will confirm your identity or reject it.

Biometric Measurements

There are two types of biometric measurements, namely, physiological and behavioral. The many approaches are constantly being refined and are the basis for learning and improvement in researches.

Physiological Identifiers

Physiological identifiers are based on the physical features of a human body and are of the following types:

DNA Recognition

A person shares 99.7% of his DNA with his biological parents, and the remaining 0.3% is variable repetitive coding. This repetitive coding is what DNA biometrics works on via genetic profiling or genetic fingerprinting, where unique repetitive DNA regions are isolated and identified.

Ear Recognition

Since a person’s ear structure does change radically over time, ear images are a biometric measurement. Ears also fulfill the four key biometric traits – uniqueness, permanence, collectability, and universality.

Iris Scanning

Iris recognition is the technique of taking a high-contrast image of a person’s iris using visible and near-infrared light.

Retina Recognition

Retina recognition uses a person’s unique retinal patterns to identify them. The individual must line up a sequence of markers that are visible via the eyepiece. The uniqueness of the blood vessel patterns is used in retina identification.

Face Recognition

Face recognition is used for recognizing or validating an individual’s identification by capturing a digital image of their face through pictures, videos, or in real-time.

Fingerprinting

The automated process of recognizing or verifying an individual’s identification based on the comparison of two fingerprints is known as fingerprint recognition.

Finger Geometry Recognition

Finger geometry recognition uses the unique geometric characteristics of the fingers to distinguish people automatically. To achieve personal authentication, finger geometry biometric systems use characteristics including finger length, fingerbreadth, finger area, and finger thickness.

Hand Geometry

Hand geometry recognition uses variables like palm width, finer length, finger width, finger area, and finger thickness.

Odour Recognition

Scent recognition works on identifying individuals based on unique chemical patterns.

Vein Recognition

Vascular biometrics or vein recognition detects portions of a person’s circulatory system unique to each person. Optical biometric scanning devices are used to collect images of veins in palms, eyes, or fingers.

Behavioral identifiers

Behavioral identifiers are based on the patterns of human activities and are of the following types:

Gait Recognition

A person can be identified for gait recognition by extracting gait characteristics from a scene, image, or video.

Keystroke Recognition

The uniqueness of Key-Down and Key-Up are used to identify the identity of a person.

Voice Biometrics

Voice biometrics is a technique that uses voice pattern recognition to authenticate an individual’s identification.

Signature Recognition

Signature recognition uses a person’s handwriting in their signature to identify them. There are two different approaches to this type of behavioral biometrics, namely Static and Dynamic.

History of Biometrics

Though some of the first instances of biometrics can be traced back to 500BC in the Babylonian empire, biometrics were first recorded in the early 19th century through a biometric identification system developed by Alphonse Bertillon to identify and compare criminals. Though there were limitations in this system, it set the pace for biometrics identification and authentication.

In the late 19th century, fingerprinting was developed to fulfill two aims, identification of criminals and contract signatures. This was when the uniqueness of a person’s fingerprint pattern was recognized. Edward Henry is known for developing the Henry Classification System, a fingerprinting standard.

This was the first method for identifying people using fingerprints’ unique structures. Law enforcement immediately adopted the technique, which swiftly replaced Bertillon’s methods and became the industry standard for criminal identification. The development further sparked a century of study into what additional physiological features might be used to identify people.

Advances in Biometrics Over the Years

Biometrics as an area of study expanded at a rapid pace during the next decades. Below are some of the main advancements that contributed significantly to the field of biometrics:

• Semi-automated facial recognition systems were created in the 1960s, and they required administrators to evaluate facial features in images and extract useable feature points.
• By 1970, the FBI had begun allocating funds for advancing and developing fingerprint and face recognition. This sparked the development of increasingly advanced biometric capture, data extraction, and biometric fingerprint devices.
• The National Institute of Standards and Technologies established a Voice division in the 1980s to research and advance speech recognition technology. This stage helped lay the foundation for current voice recognition approaches.
• The idea that irises, like fingerprints, are unique to each individual was presented in1985, and the first iris identification algorithm was patented in 1994. It was also recognized that blood vessels in the eyes could be used as a unique identification variable./li>
• Face detection technology was created in1991, allowing for real-time recognition. Even though these algorithms had several flaws, they sparked a surge of interest in facial recognition research.
• In the early 21st century, the United States was witnessing hundreds of patented and functioning biometric systems. Biometrics were not only being used just in major corporations and by the government; they were also used in commercial items and large-scale events such as the 2001 Super Bowl.

Who Uses Biometric Devices?

Biometrics has mainly found its applications in law enforcement and military access control. However, in the last decade, we have witnessed biometrics becoming more prevalent in our daily lives.

Owing to the advancements in biometric technology, it’s now uncommon that we don’t come into contact with some sort of biometric application. This is evident from our usage of smartphones that help in checking the weather, logging in through fingerprint and facial recognition, and more. We are surrounded by biometric technology.

Following is a list of what devices use biometric technology:

• Public safety and law enforcement through recognition and verification of criminals
• Military through identifying enemies and allies
• Control of the border, travel, and migration through identification of travelers, migrants, and passengers
• Civil identification of citizens, residents, and voters
• Healthcare and subsidies identification
• Logical and physical access through identification of parties involved
• Commercial uses through identification of consumers

Civil Security

In this case, law enforcement agencies use biometric systems for law enforcement activities and covert criminal I.D. solutions, including Automated Fingerprint (and palm print) Identification Systems (AFIS). All data, including fingerprint, palmprint, and subject records, are stored in a database, from which they can be further searched and collected.

In the present times, Automated Biometric Identification System (ABIS) is utilized for biometric identification, authentication, and deduplication on large scales by comparing a sample to different samples in the database.

Recently, live facial recognition has gained popularity for recognizing people in a crowd in real-time or after an incident. Its aim is public security in cities, airports, border crossings, and other sensitive areas like stadiums and places of worship.

Military Needs

The military has also expanded its use of biometrics.

The U.S. Army’s wearable biometric devices, such as identification tokens, which allow identity authentication, have continuously improved. The portable identification tokens integrate public-key-based credentials with developments in the commercial wireless financial sector and flexible hybrid electronics.

The Army Research Laboratory (ARL) in the United States has performed experiments that merge facial recognition software with thermal imaging to help soldiers locate people of interest in areas devoid of light. This is carried out by sensing radiated heat from the person’s skin.

With the latest software upgrade, the U.S. Army has updated a 20-year-old biometric database to assist personnel guarding at crossings in identifying people of interest in real-time.

Border & Migration Control

A biometric passport or an e-Passport holds an electronic microprocessor chip within it with data related to the passport holder. Several nations are working to granting people biometric passports. The first country to officially offer these passports was Malaysia in 1998. By mid-2019, 150 countries were actively providing them, and by 2020 1.2 billion digital passports had were being actively used.

Currently, fingerprinting, facial recognition, and iris recognition are being used for this category. The International Civil Aviation Organization’s (ICAO) Doc 9303 (ICAO9303) describes the document and chip features, biometric file formats, and communication protocols. The chip contains only the image of every biometric feature, and electronic border control systems carry out their comparison.

Civil Identification

Databases such as the AFIS (Automated Fingerprint Identification System) are connected to the civil registration records. This enables governments to identify each citizen uniquely.

A major example of such a project is India’s Aadhaar Card project. The Aadhaar card contains a unique 12-digit number provided to all citizens who have applied for the same. It is not equivalent to Indian citizenship in any way but allows reliable and quick identification and authentication of the Aadhaar cardholder.

The number provided to an individual is based on unique biometric features, such as fingerprints, facial images, and iris scans. The number can be linked to mobile numbers, bank account numbers, public subsidies, education, unemployment benefit schemes, and more.

Healthcare

Biometrics in healthcare is used to ensure precise patient verification and supervision at medical offices, clinics, and other medical centers. Examples include authorization control and patient databases. Biometrics may be used to monitor patients outside of typical healthcare settings, and biometrics is also used to build new applications such as electronic prescriptions and remote diagnostics.

The healthcare industry has begun recognizing the need for biometric I.D. cards in which patients are identified based on biologically distinct variables such as facial, fingerprint patterns, irises, and audio. This approach guarantees that the correct individuals get the appropriate care, making global healthcare safer and more successful.

Access Control

Using biometric access control systems, unwanted and unauthorized individuals are denied access and entry into physical spaces (physical access control) and applications (logical access control).

Access cards, OTPs, codes, and static passwords are based on temporary data that people have, which can easily be discarded. However, biometric access control systems are based on data of who people are. Manufacturers of biometric devices are increasingly equipping mobile models with biometric access control features like fingerprint and facial recognition systems. In 2013, iPhone 5 was the first smartphone to bring fingerprint recognition into the mobile market, and later iPhone X popularised facial recognition.

Commercial Applications

Commercial applications of biometrics include KYC, Aadhaar, etc. Organizations such as banks, fintech, telecom operators, etc., use biometric technology to make KYC (Know Your Customer) procedures for clients even more efficient and simple to use. These institutions utilize KYC processes to gather and validate their clients’ identities to confirm their authorization for solutions.

As the coronavirus pandemic hit services over the previous two years, essential onboarding services such as identity verification are being developed based on facial recognition.

Trends and Future of Biometrics

Researchers have been working on solving the drawbacks and limitations of biometrics applications and systems currently in use to advance the biometrics industry. Common issues include data inaccuracy and biometric spoofing. Therefore, the following are some directions in which research is being carried out.

Image Compression for Face and Fingerprint Recognition Systems

The United States Military Academy is developing an algorithm based on uniqueness. This model will train itself to identify individuals through their unique characteristics and features, such as how a person interacts with a computing device, typing dynamics, common actions, grammatical errors, and similar actions that are unique to the person. Therefore, considering these features, each person will have a unique profile highlighting their behavioral and stylometric details. Such data can be extremely challenging to duplicate or forge.

Biometric Liveness Detection Technique

Recently, an innovative approach by Kenneth Okeareafor depicted an application of biometric liveness detection technique with trait randomization that offers optimization and security in its design. This has potentially paved the way for decreasing the severity of biometric spoofing and increasing its accuracy.

A simulation of the subject algorithm was developed through a 3D multi-biometric framework. The framework included 15 variables, including iris scans, fingerprint patterns, and facial images. The simulation containing 125 unique randomization combinations outputted an accuracy of 99.2%. Okereafor’s concept is distinctive in that it uses uncorrelated biometric characteristic parameters such as blinking frequency, pulse oximetry, ECG, fingers spectroscopy, sweat, and other inherent and instinctive biological features.

Posterior Authentication

Japanese researchers developed a biometric system with 400 sensors embedded within a chair. The chair, when activated, will measure a person’s contours and pressure points. The biometric authentication system is said to provide 98% accurate results. It can also find application in anti-theft systems in cars.

Pixel Stack to Record Multi-Biometrics

Lawrence F. Glaser invented a technology that uses pixel stacks to achieve a sequence of objectives, culminating in the recording of a multi-biometric. The device is the first of its kind. It can simultaneously capture two or more unique biometrics from the same patch of pixel surface, enabling the data to build a third biometric. This complicated arrangement includes data alignment. For instance, collecting the fingerprint and the capillary pattern simultaneously.

There are other potential applications of this technology, such as collecting bone data and its status during an event. The technology does not require RGB (RED GREEN BLUE) surface emissions since pixel stacking in minimum surface area is merged with the feature of any color emission from a single pixel. Magnetic data can be conveyed once devices such as smart cards automatically sense user activity. The technology can even detect movement from a distance.

Is Biometrics Reliable: Security Aspects of Biometric Devices

Computing devices and software pose the potential risk of data leakage. Sensitive and vital information such as audio records, fingerprint pattern scans, facial images, etc., if leaked from servers and networks. False positives and false negatives are also real possibilities. A user who is wearing makeup, mask, or spectacles, or ill or tired, may be missed by a face recognition system.

Companies should employ various kinds of authentication simultaneously, according to experts, and escalate swiftly if they notice warning indications so that they may have time to move to a backup authentication mechanism or a second communication channel.

Some consumers may object to firms gathering information about their phone usage patterns, such as the time of day and geolocation. If this information becomes public, it might be utilized by stalkers or tabloid journalists. Authoritarian social structures or outgrowing criminal prosecutors might likewise misuse the information. Marketers and advertising that aren’t honest may do the same.

Any of these scenarios may result in severe public shame, regulatory fines, or class-action lawsuits for the corporation that gathered the data. If DNA scans become more widely used, they will open up a whole new world of privacy problems, such as exposing medical disorders and familial ties.

This is why biometric data security is of utmost importance, perhaps more so than password security, because passwords may be readily altered if revealed, but biometric aspects are tough to duplicate. A fingerprint, ear image, iris scan, or retinal scan are all irreversible. Any leak of any biometric variable may put consumers in danger indefinitely and expose the corporation that loses the data to severe legal liability.

A key decision here would be to select the vendor which provides authentication technology wisely. Furthermore, firms that do not retain credentials on file are protected by the law. Security procedures of the best quality should be used if a firm has to gather authentication data and present it on its systems. Encryption procedures are applied for both the stages – at rest and in transit. Runtime encryption, which maintains data secured even as utilized, is now possible with the latest technology.

Biometrics Market and Industry Report

The global biometrics market was $23.4 million in 2018, and by 2024, it is estimated to expand to $71.6% at an average growth rate of 23.2% per year, as reported by BBC Research. The biometrics market size is estimated to reach $1.1 billion by 2024. The technologies leading this growth would be fingerprinting, face recognition, vein recognition, iris, and audio recognition.

Trends in Biometrics Market

The following trends will be seen in the biometrics sphere:

• Paperless self-boarding systems are projected to replace biometric CCTV and ACS systems.
• Development of card-less payment technology in sporting facilities via payment offices.
• The banking industry would contain payment technology with remote customer verification.
• Hotels, stores, and restaurants would have employee time tracking, biometric payments, etc.

How Accurate Is Biometrics in 2021?

Biometrics places a premium on accuracy. Passwords are still popular since they are permanent. However, biometrics may alter (adolescents and facial injuries can cause people’s voices to get louder and their faces misread, resulting in data scans).

Barclays stated that their speech recognition technology has a 95 percent accuracy rate when tested. While these numbers are correct, they indicate that many of their customers’ voices have not been recognized by the system. Because of the uncertainty around these systems, people may be hesitant to utilize various biometric devices instead of traditional password-based techniques.

What Are the Pros and Cons of Biometric Devices

Following are the advantages and disadvantages of biometric devices:

Pros of Biometric Devices

Regardless of the method used, the commonality of all these biometric technologies is that they contain human characteristics:

• Universality because they can be found in all individuals
• Unique because they allow one person to be distinguished from another
• Permanent, because they remain the same
• It is possible to record (with or without consent)
• Measurable, allowing for comparisons in the future
• Forgery-proof (facial and fingerprint patterns)

Cons of Biometric Devices

Biometric security provides many advantages for accurate verification and identity, but it’s not without its criticism, mainly regarding people’s privacy and their capacity to handle their personal information. The risk may be divided into two categories:

• Use of biometrics information for any reason other than those approved by the public, such as as a service provider or to prevent fraud. Suppose the biometric information belongs to a third party. In that case, it can be used for reasons other than those for which the interested party gave authorization, resulting in the availability of biometric information linked with a file other than the one intended.
• As data is transmitted to a central database, it is logged and fraudulently copied in subsequent transactions.

People lose privacy as a consequence, and data security issues arise. Data protection authorities seem to favor solutions that use distributed datasets.

What Is a Cross-Context Attack in Biometric Devices

Attacks against behavioral biometrics are becoming more common. Many studies have focused on equipping biometric sensors with vectors of previously predicted properties, and attackers often train themselves to adapt to the victim’s behavior.

Obtaining biometric information on a victim, on the other hand, might be challenging, especially if validator data is properly secured. An attacker would have to get the data from somewhere else if they didn’t have access to authentication. This is called a cross-attack in biometric devices.

Biometric Cards and Tokens

In biometrics, two similar algorithms cannot be compared. This is because two biometric measures may be compared as plain text. In some situations, the data is not processed by the device memory. As a result, only secure equipment should be used for biometric testing.

This approach, in a nutshell, necessitates a central monitoring server, trusted essential devices, or personal security fixes.

Tokens and smart I.D. cards are the best options to be used with biometric systems.

Documents

List of technical documentation that we are referring to when writing this article:

• Ear Biometrics: A Small Look at the Process of Ear Recognition
• Human Ear Recognition Using Geometrical Features Extraction
• Retina Recognition
• Hand Geometry Recognition
• Gait Recognition: The Wearable Solution
• Keystroke Recognition
• Military Taking Biometrics to a New Level
• Doc 9303 Machine Readable Travel Documents Part 3: Specifications Common to all MRTDs Eighth Edition, 2021
• When Your Fitness Tracker Betrays You: Quantifying the Predictability of Biometric Features Across Contexts

Conclusion

Over recent years, biometric devices have been widely adopted by governments as well as the private sector. These devices offer several advantages over traditional identification and authentication systems. Consequently, they have found applications in various industries. However, there are some drawbacks as well on which researchers are working.

Key points:

• Biometric is not a new concept and dates back to 500 BC.
• Fingerprinting is the most common biometrics technology and mainly uses four types of sensors – optical, capacitive, ultrasonic, and thermal.
• Biometric devices are of two types – identification and authentication devices.
• Biometric devices and their uses are found in law enforcement, military, border and mitigation control, civil identification, healthcare, physical and logical access, and commercial applications.
• Researchers are actively targeting drawbacks to improve this technology.
• To opt for secure biometric devices, companies should choose their authentication provider wisely.
• By 2024, the global biometrics industry is estimated to expand to $71.6 billion. The biometrics industry is estimated to be $1.1 billion.

FAQ

What Is CER in Biometric Devices?

CER refers to the crossover error rate, which tells the biometric system’s overall accuracy. It is the point where the False Reject Rate (FRR) intersects the False Accept Rate (FAR). At this point, FRR equals FAR. CER is also called Equal Error Rate (EER).

How Do Biometric Devices Help Improve Security?

Biometric devices focus on unique behavioral and physiological aspects of a person, which are hard to duplicate. Companies use biometrics to implement an easy-to-use and secure solution which removes password risks and enhances overall access control.

How Popular Are Biometric Devices?

Biometric devices are gaining popularity in several global industries owing to the level of security they provide. More than 75% of the U.S. uses biometric technology in one or the other, with the major use being biometrics in smartphones, such as fingerprint sensors, facial recognition, voice recognition, etc.

What Are Biometric Devices Used For?

The main uses of biometric systems and devices are identification and authentication. Biometric devices are most commonly used in security, banking, mobile access and authentication, law enforcement, public transports, schools, home assistants, and building access.