Biometric Authentication Now and Then: History and Timeline

From ancient ways of personal identification, in which people had limited options to identify others, we have come to the era of computer vision and biometrics, which does not require any external artefact or token to identify others. With biometrics, an individual can be identified with his/her own biological or behavioural characteristics, instead of his/her associations, possessions or any secret information.

The need of accurate identification led us to biometrics, which leverages technology to expedite the process of human identification and authentication.

From printed IDs, we have come to the biometric ID, which lets you prove your identity without carrying any card or document. Biometric security is evident everywhere. At airports, public places, workplaces office and even on your smartphone, biometric authentication is now a commonplace.

But how did we reach there? How this extraordinary journey of biometrics started and how did it attain today’s level of ubiquity. This articles covers history, timeline and where has biometrics reached today.

Biometrics, which was once seen either in Sci-Fi movies or used in forensics applications, is now a commonplace. So common that people who own a smartphone, leverages one or more biometric recognition methods.

Biometrics is a technology that leverages human beings’ very own anatomical, chemical or behavioral characteristics to identify them. Human beings’ own characteristics are naturally used for person to person identification as well. We can recognize our friends, family and a familiar person by their face or voice. In case of biometrics, this ability is given to electronic equipment to identify us without the help of any human assistance.

Some human physiological characteristics like Fingerprints, iris patters, retina pattern, vascular patterns, face geometry, hand geometry, etc. are considered to be unique for an individual. So these characteristics are taken as biometric identifiers. Along with these physiological characteristics, there are behavioral characteristics like gait, key stroke dynamics, signature, voice, etc. that are also considered individual characteristics and can be leveraged for biometric identification.

There are several types of characteristics found in anatomy, chemistry and behavior of the human beings, which can be leveraged to uniquely identify an individual. These biometric types are categorized in the following:

These characteristics or patterns are found in or on human body, e.g. patterns found in fingerprints, iris, retina, DNA structure, etc.

These characteristics or patterns are found in behavior of an individual, e.g. gait, signature dynamics, keystroke dynamics, patterns of using smartphones, etc.

Authentication is the act of confirming the validity of an attribute of a single piece of data provided and claimed true by an entity. When this confirmation of validity is done using biometrics of a person making the claim, it is called biometric authentication.

Biometric systems are the system that can acquire, process, and match one or more biometric identifiers. Biometric systems can be standalone systems consisting dedicated hardware and software to perform a specific task (e.g. fingerprint attendance machine) or they may be computerised systems to run different applications to perform different biometric operations like identification, analysis, management, etc. (e.g. AFIS and IAFIS).

These systems are designed to capture and process a single biometric identifier, e.g. fingerprint recognition systems, face recognition systems, etc. These systems may fall short in “population coverage” as not all individuals in target population may have that particular biometric identifier in usable condition.

These systems make use of more than one biometric characteristics to identify or authenticate a subject. Since these systems do not rely on just one biometric identifier, they provide better population coverage. People with a biometric identifier in unusable condition may present the other one that can be scanned by the system.

Security controls laid with the help of biometric recognition technology is called biometric security. When you replace your old school mechanical key door lock with a fingerprint lock, biometric security is what you deploy. Biometric security can be deployed to control physical access, e.g. door access, as well as to control digital access like PC logins, online accounts, etc.

Commonly, the term “ID” refers to a government issued valid ID card. These IDs serve as a tool of identity verification, i.e. they can help you prove who you are. Just like those printed IDs, a biometric ID, is also a mean of identity verification, the difference is that you do not have to rely on a card, document or any external object to prove your identity. Your biometrics like fingerprint, iris pattern, etc., are used as an ID instead.

Biometric ID is considered superior than printed IDs. Printed IDs can be highly vulnerable to manipulation. They can be shared by similar looking people. Computer based editing and printing technology has made ID manipulation as easy as child’s play, resulting increasing numbers of cases of identity fraud. In such scenarios a biometric ID can do the job of trusted identity verification.

Biometric systems capture physical or behavioural characteristics using different sensing and imaging techniques. Biometric systems capture this data in digital form, just like today’s computers or smartphones and it is also stored or transmitted in digital form. This human physiological or behavioral data captured through a biometric system is called biometric data. Most biometric systems are equipped with built-in mechanism such as encryption, for the security of biometric data.

Due to increasing use in civil identification applications and consumer electronics like phones and computers, biometrics may seem as if it has emerged in recent years, the technology, however, is quite old and its roots dates back to 500BC.

Thumbprints are mentioned in ancient Indian text written by Hindu sage Agastya, who is believed to be able to predict past, present and future lives of an individual by reading his/her thumb print.

There are evidences that Babylonians used fingerprints to record business transactions on clay tablets. Fingerprints served as a proof for the parties involved in the transaction. Fingerprints are also found on their pottery and seals.

In Qin and Han Dynasties (221 BC – 220 AD), there are findings that indicate the use of handprints as evidence. Historic records from Qin Dynasty also mention use of handprints for the theft crime investigations.

Handprints were also used as evidence in some criminal trials of theft in china during AD 300. Kia Kung-Yen, a Chinese historian also mentioned that fingerprints can be leveraged for verification.

In a Persian book “Jaamehol-Tawarikh” (means Universal History), written by Rashid-al-Din Hamadani (also known as “Rashideddin”, 1247–1318) in 14^th century, the author commented about the Chinese practice of personal identification using fingerprints.

Dr. Nehemiah Grew (1641 – 1712), an English plant anatomist and physiologist, who is also known as the “Father of Plant Anatomy” published friction ridge skin observations in his paper “Philosophical Transactions of the Royal Society of London” in 1684. Dutch anatomist Govard Bidloo detailed friction ridges in his book “Anatomy of the Human Body” in 1685.

Marcello Malpighi (1628 – 1694), an Italian biologist and physician, who is also called the founder of microscopical anatomy and histology, mentioned fingerprint ridges, spirals and loops in his literature. The innermost layer of the epidermis of skin was named after him.

Until late 1700s, there was no mention for the uniqueness of fingerprints. In 1788, Johann Christoph Andreas Mayer (1747–1801), a German anatomist made first of such statement in his book Anatomical Copper-plates with Appropriate Explanations.

Mayer was the first to mention the uniqueness of friction ridges.

19^th century witnessed some major breakthroughs in the field of biometrics including rise and fall of Bertillon System, development of fingerprint classification system, use of fingerprint in crime scene investigations and establishment of fingerprint bureaus.

Jan Evangelista Purkyně or Purkinje mentioned nine types of fingerprints patterns in his thesis published in 1823. However, there was no mention of usage of fingerprint patterns in personal identification.

Hermann Welcker, German anthropologist from the University of Halle acknowledged that fingerprint patterns are permanent. He conducted the study on his own fingerprints by taking handprint in 1856 and again in 1897. He published his observations in 1898.

In 1858, Sir William Herschel, while working as a chief magistrate of the Hooghly district in Jungipoor, India, started recording handprints on legal contracts. According to the englishman, the purpose of printing handprint on the contracts was to frighten the other party. From there, Herschel started collecting handprints and later fingerprints while writing contracts with locals. Personal identification was not at all the objective behind this collection.

Locals also superstitiously believed that handprints or fingerprints made the contract more binding rather just signing it. So the motive behind this biometric collection was more superstitious than scientific.

In 1863, Paul-Jean Coulier, a professor for chemistry at Val-de-Grâce military hospital in Paris discovered that iodine fumes can help reveal latent prints on paper. He also showed how these prints can be persevered.

In 1877, The American Journal of Microscopy and Popular Science included the following excerpt from a lecture.

During the 1870s, a major contribution in fingerprint biometrics came from Dr. Henry Faulds, a Scottish surgeon in a hospital of Tokyo city, Japan. In his paper published in the scientific journal Nature, he explained how fingerprints can be useful in personal identification and also proposed a method of recording them with ink. He was the first to identify a fingerprint left on a vial. He also proposed a classification system for fingerprints.

In 1886, Dr. Henry Faulds contacted Charles Darwin with details of his work, but Darwin was too old to work on it, so he transferred Dr. Faulds’ work to his cousin, Francis Galton. Francis Galton later published a detailed statistical model of fingerprint analysis and identification in his book Finger Prints. He also encouraged usage of fingerprints in crime scene investigations and criminal identification.

Just when fingerprint recognition was trying to come out of its infancy, Alphonse Bertillon, a French police officer, who was also a biometrics researcher, proposed a personal identification method based on physical measurements. Alphonse Bertillon’s unique approach to anthropological techniques is considered the first scientific approach for criminal identification. This system consisted of five initial measurements — head length, head breadth, length of middle finger, length of the left foot, and length of the cubit. Bertillon system was later supplanted by fingerprint recognition.

An Argentine law enforcement officer Juan Vucetich started filing fingerprints with a self-created fingerprint recording method. He associated these fingerprints with anthropometric system that Alphonse Bertillon had already proposed for better accuracy in identification. He is also known for establishing the world’s first fingerprint bureau in 1892 following the statistical model of fingerprint analysis proposed by Francis Galton.

In the same year, fingerprints helped solve a crime mystery in the Argentinian city Necochea, in which a mother murdered her two sons and accused the neighbour, despite the brutal interrogation the neighbour did not confess to the crime. The investigation officer, who was also a colleague of Juan Vucetich, found a thumb print on the crime scene. Upon analysis, the print matched with the right thumb of the mother of deceased kids and later she confessed killing them. This case proved the superiority of fingerprints over anthropometry for the purpose of crime scene identification.

Francisca Rojas, the murderer of her own kids, became the first criminal brought to justice with fingerprint matching.

Following the approval by the Council of the Governor General, a committee report resulted in establishment of a fingerprint bureau in Calcutta (now Kolkata), India. The report had proposed use of fingerprints for the identification and classification of criminal records and the approval paved the way to the formation of Calcutta Anthropometric Bureau in 1897.

Indian fingerprint experts Azizul Haque and Hem Chandra Bose, who were working at the bureau in the supervision of Sir Edward Richard Henry, worked on a fingerprint classification system. This system was called Henry Classification System, named after Sir Edward Richard Henry.

20^th century witnessed some major breakthroughs in biometrics. Early years of 1900s established fingerprint biometrics as a credible biometric method. This century also witnessed more human characteristics for personal identification expending the horizon of biometrics.

After India, Henry fingerprint classification system was later accepted in England and Wales upon the formation of UK’s first Fingerprint Bureau in Scotland Yard, headquarters of the Metropolitan Police Service (MPS) in 1901.

Henry Classification System was used in fingerprint identification for around hundred years and became the basis of modern day automated fingering identification system (AFIS). After 1990s, ridge flow classification approaches has taken over Henry Classification System.

In 1902, Dr. Henry P. DeForrest, pioneered the idea of fingerprinting in the New York Civil Services to prevent identity fraud during exams. In 1903, two inmates in Leavenworth Prison System named Will West and William West found to have nearly identical Bertillon measurements, and bore a striking resemblance. This incident rendered reliability of the Bertillon system questionable.

Fingerprints of Will and William West, however, found to be different. This incident drastically impacted the reliability of Bertillon system and it began to decline. In 1904, the St. Louis, Missouri Police Department and United States Penitentiary at Leavenworth, Kansas introduced fingerprinting by forming fingerprint bureaus.

US Army started using fingerprints in 1905. Two years later, the US Navy and then US Marine Corps in 1908 also adopted fingerprinting.

An act enacted by the US congress resulted in establishment of identification division of the FBI. National Bureau of Criminal Identification of International Association of Chiefs of Police (IACP) and Bureau of Criminal Identification of US Justice Department consolidated to form the identification division.

In 1936, Frank Burch (1876-1957), an ophthalmologist from the United States, conceived the concept of iris pattern for personal identification.

In 1949, a British ophthalmologist J.H. Doggart, wrote that:

In a 1953, F.H. Adler mentioned in Physiology of the Eye, a clinical textbook written by him:

Woodrow Wilson Bledsoe, an American mathematician and computer scientist, started working on facial measurement. He developed a system using RAND tablet that could manually classify photos of faces. RAND Tablet is a graphical computer input device, which is one of the earliest digital graphic devices. Bledsoe used RAND tablet to input horizontal and vertical coordinates on a grid using a stylus that emitted electromagnetic pulses. Coordinate locations of different facial features like eyes, nose, hairline and mouth could be recorded manually with Bledsoe’s method.

Carl Gunnar Michael Fant (1919-2009), a professor emeritus at the Royal Institute of Technology (KTH) in Stockholm, published the source-filter model of speech production in 1960. His acoustic speech production model explained the physiological components of acoustic speech production. Gunnar Fan’s research and model was based on x-ray analysis of people making a particular phonic sound. Gunnar Fant’s Orator Verbis Electris (OVE) system was able to produce lifelike speech synthesis.

Hughes published a research paper on automation of fingerprint recognition.

First signature recognition system was developed by North American Aviation in 1965.

FBI (Federal Bureau of Investigation) started putting significant efforts and manpower in developing an automated system for fingerprint recognition. A contract for the research on automation of fingerprint recognition was given to National Institute of Standards and Technology (NIST) by the FBI in 1969.

Research in the direction of signature recognition continued in 1970s. However, research during this decade was more focused on dynamic characteristics of signatures (how signatures are made) rather than static characteristics (design of the signature).

Dr. Joseph Perkell expanded the original model of acoustic speech production developed by Gunnar Fant. His model of acoustic speech production detailed the complex behavioural components along with biological elements of speech production.

Hand geometry recognition became the second biometric modality, which had commercially available recognition systems after the fingerprint recognition.

A few employees from Hertfordshire (United Kingdom) Fingerprint Bureau started organizing fingerprint experts throughout the UK in 1974. Their efforts paved the way to formation of the country’s first professional fingerprint organization, the National Society of Fingerprint Officers. The organization also attracted fingerprint experts throughout the world and eventually became The Fingerprint Society in 1977.

In 1975, FBI started pushing forward fingerprint recognition by funding the development of fingerprint sensors and minutiae extracting methods. Due to high cost of digital storage back then, only the minutiae were stored while processing fingerprints. The fingerprint machine algorithm M40 developed by NIST became the first operational algorithm used by the FBI.

Following their efforts in 1970s, Harmon, Goldstein and Lesk were able to add increased accuracy to a manual facial recognition system. They used 21 specific subjective markers including lip thickness and hair color in order to identify faces automatically. As with Bledsoe’s system, the actual biometrics had to still be manually computed.

World’s first speaker recognition prototype was developed by Texas Instruments, an American semiconductor and IC manufacturer, in 1976.

Institution of the world’s first certification program for fingerprint experts was agreed by voting of delegates to the 62nd Annual Conference of the International Association for Identification (IAI) on 1 August 1977 at New Orleans, Louisiana.

A patent was granted to Veripen, Inc., for developing a system that was able to capture dynamic information from a signature. This “personal identification apparatus” (as it was named in patent filing) was able to capture pressure data while signing.

The National Institute of Standards and Technology (NIST) form a dedicated division named Speech Group to encourage the development of voice recognition (speech recognition and speaker recognition) technology.

John Gustav Daugman, a British-American professor of computer vision and pattern recognition at the University of Cambridge, started working on iris recognition in 1980s. He filed for a patent for his iris recognition system in 1991 while working with the University of Cambridge. John Daugman’s iris recognition algorithm was able to recognize people in real time by encoding iris pattern from some distance.

Daugman’s iris recognition went commercial in late 1990s and turned out to be a huge success. It was used in many small as well as large scale iris recognition campaigns.

• Aadhaar biometric registration in India to enroll its 1.3 billion citizens with iris and other biometrics.
• Border security controls with iris recognition in UAE.
• Passport free immigration in many countries including the USA, the UK and Canada.

Although a patent had been awarded by the US patent office to Robert P. Miller in the late 1960’s and early 1970’s for a hand recognition device. This device could measure hand characteristics and record unique features for comparison and ID verification. Miller’s device, however, was highly mechanical and manufactured under the name “Identimation”.

Several other companies launched development and manufacturing efforts during the 70s and early 80s. In the mid-1980s, David Sidlauskas developed and patented an electronic hand scanning device and established the Recognition Systems, Inc. of Campbell, California in 1986.

In 1985, vascular pattern recognition method devised by Joseph Rice was awarded a patent. Rice’s recognition system leveraged the pattern formed by subcutaneous blood vessel to identify a subject.

In 1986, Aran Safir and Dr. Leonard Flom presented a concept that patterns formed by iris muscles are unique and can be used for personal recognition.

Matthew Turk and Alex Pentland found that eigenfaces could enable computer vision to identify subjects in real time. Eigenfaces is the name given to a set of eigenvectors when they are used in the computer vision problem of human face recognition. Facial recognition with eigenfaces was originally developed by Sirovich and Kirby in 1987.

Owing to its efficiency and accuracy, John Daugman’s iris recognition algorithm was a commercial success. It was used in wide variety of applications including large scale biometric enrolments. This algorithm was tested in many field and laboratory trials, producing no false matches in several million comparison tests.

In 1994, John Daugman patented basis for iris recognition and its underlying computer vision algorithms for image processing, feature extraction, and matching, and published the paper “High confidence visual recognition of persons by a test of statistical independence” in IEEE Transactions on Pattern Analysis and Machine Intelligence.

Hand geometry was used in Atlanta Olympic Games 1996 to protect the Olympic village from any unauthorized entry. More than 65,000 people were enrolled to use the system and over 1 million transactions were processed by these systems during the Olympic Games.

Human Authentication API (HA-API), the first commercial, generic biometric interoperability standard, was published in 1997. It led to vendor independence and interchangeability by allowing easy integration between different products manufactured by different vendors / manufacturers.

The FBI (Federal Bureau of Investigation) launched Combined DNA Index System (CODIS). This system could store, search and retrieve DNA data.

The International Biometric Industry Association (IBIA), a non-profit industry trade association to advance the collective international interests of the biometric industry, was founded in Washington, DC.

Technical Advisory Group on Machine Readable Travel Documents (TAG / MRTD) of ICAO (International Civil Aviation Organization) initiated its study on biometrics and MTRD (Machine Readable Travel Documents) in 1999. According to ICAO, objective of study was to determine…

FBI’s large scale computerized fingerprint identification system IAFIS became operational 1999. With IAFIS, it became possible for FBI to search fingerprints collected on any system. It also made integration of different systems possible. IAFIS was able accept electronic submissions of fingerprint services (e.g. for criminal history, background check, etc.) with AFIS.

So far, 21^st century has been an astonishing journey for biometrics. Faster and more efficient systems, mobile biometric and most importantly increasing use and social acceptance are something biometrics can brag about as of late 2010s. Now people carry multiple biometric systems in their phones and rely on them to carry out financial and e-commerce transactions.

The National Biometric Security Project (NBSP) was founded in 2001 to respond to the events of September 11, 2001, and the need for accelerated development and deployment of biometrics technologies.

Face recognition was deployed at Super Bowl championship organized in January, 2001 in Tampa, Florida. It was done to identify individuals wanted by the law enforcement agencies. Unfortunately, the system misidentified several sports fans and none of them came out to be anyone wanted by the agencies.

In 2002, ISO / IEC standards committee on biometrics was established to standardize the different aspects of the technology.

Hitachi and Fujitsu launched vein biometric products in 2002. Initially doubted for its uniqueness and usability, veins eventually turned out to be one of the most consistent, discriminatory and accurate biometric trait.

Post September 11, 2001 attacks, people felt civil liberties drastically affected by the incident. Common citizens had to go through thorough security checks and public surveillance with biometrics intensified.

In her book Our Biometric Future: Facial Recognition Technology and the Culture of Surveillance, Kelly A. Gates, Associate Professor in Communication and Science Studies at University of California San Diego, identifies 9/11 as the turning point for the cultural language of our present.

In an effort to introduce biometric MRTDs (Machine Readable Travel Documents) and enhance travel security, ICAO (International Civil Aviation Organization) adopted a global, harmonized blueprint for the integration of biometrics into the MRTDs (e.g. passports, passport cards, etc.).

In order to achieve excellence in biometrics, European commission established European Biometrics Forum.

In order to enhance travel security of the domestic as well as international travel, CBP (U.S. Customs and Border Protection) agency made the US-VISIT system operational. The system could collect and analyse biometric data (e.g. face, fingerprints, etc.) and verify against the database of biometric identities of people on surveillance (e.g. criminals, illegal immigrants, terrorists, etc.) This system is now accessed by as much as 30,000 users from federal, state, and local government agencies.

US Department of Defence deployed ABIS (Automated Biometric Identification System) in 2004. ABIS can be viewed as an extended version of FBI’s IAFIS, however, unlike IAFIS, which is designed to perform fingerprint operations; ABIS can perform biometric operations on fingerprints as well as facial images, voice samples, iris patterns, and even DNA. ABIS’s primary objective is leverage biometrics to ensure national security from internal as well as external threats.

In 2006, latest algorithms for face recognition technology were evaluated for their performance at FRCG (Face Recognition Grand Challenge). FRCG was an event to promote and advance face recognition technology designed to support existing face recognition efforts in the U.S. Government.

Face recognition technology and DNA profiling was used to confirm the identity of the United States’ most wanted terrorist Osama bin Laden. With the help of biometrics, CIA was able to identify the remains of his body with 95 percent certainty.

With the launch of iPhone 5s in 2013, Apple introduced Touch ID, a fingerprint recognition solution, which consisted of a capacitive sensor embedded on the device’s home button and underlying software that could perform fingerprint enrollment and authentication. It is not the first time that a mobile phone manufacturer had tried its luck in mobile biometrics; however, efforts prior to Apple’s were not so well organized and publicised.

With initial mixed reactions, fingerprint solution on iPhone 5s was eventually a success. It encouraged other manufacturers to come up with their take on mobile biometrics and soon the market flooded with phones with biometric recognition.

Popular biometric recognition methods like fingerprints or iris recognition are still touted as “high-tech”. However, these high tech methods may start feeling like “old-school” in coming years. In recent times, biometrics based on brain (electroencephalogram) and heart (electrocardiogram) signals have emerged.

For example, Nymi band is a wearable authentication device, on which you need to authenticate once with your heartbeat and you can remain in authenticated states once in. Commercial brainwave authentication is yet to see light of day.

On-going research has proved that biological signals from brain and heartbeat are unique to an individual and they can be used as a password or to lay access control. Some manufactures and start-ups are coming up with the innovative products with biological signal biometrics.

Rise of the smartphones and their increased share in performing banking, financial and ecommerce transactions have rendered them vulnerable to theft, fraud and cybercrime. It made service providers to look for newer countermeasures of user and data security, which paved the way for continuous authentication.

Continuous authentication is an authentication approach, which can be implemented along with traditional authentication with passwords or physiological biometrics (e.g. fingerprint, iris, etc.). Once use crosses initial authentication barrier with password / biometrics, usage pattern is profiled to check for any unusual activity.

As of mid-2010s, machine learning and artificial intelligence were hard at work to make technology based system smart and biometrics was not an exceptions.

Biometric systems had started using cutting edge machine learning and big data technologies to improve security as well as the system performance. User Behavior Analytics (UBA), an approach based on user behavior uses big data and advanced algorithms to assess user risk.

With machine learning and artificial intelligence, biometric systems can analyse the vast fields of data they collect. Machine learning is particularly useful in behavioural biometrics, in which key signal features collected by the system are modelled for each user, allowing individuals to differentiate from each other. With the help of machine learning and deep learning, biometric systems can also understand the variation in biometric samples or user behavior, making the authentication more reliable.

At Consumer Electronics Show 2018, Chinese start-up Byton introduced an electric vehicle that uses face biometrics to recognize its driver. It automatically unlocks the door and loads the driver profile when as soon as you get behind the wheel. The EV also uses voice and gesture to control several features of the vehicle.

In 2018, the South Korean car maker announced an SUV with integrated biometric solution, which allows the driver to unlock the vehicle and start the engine using fingerprint recognition. Hyundai’s fingerprint solution offers more than just unlocking the door or starting the engine. You can save your preference like seat height, angle of rear view mirrors, etc. with your fingerprint and once your car recognizes it’s you, it automatically makes adjustments.

India’s biometric identity scheme for its citizens holds biometric data of more than 1.2 billion people as of 2018. Biometric data includes fingerprints, iris pattern and face geometry of the Indian citizens. The scheme was implemented for targeted delivery of government benefits, subsidiaries and services. Since its implementation, Aadhaar has been criticized for lack of proper data protection measures and several incidents of data leak.

In 2018, Vivo, a Chinese mobile phone manufacturer launched world’s first phone with under-display fingerprint sensor. The optical sensor resides beneath the phone screen enabling the display to capture fingerprints. Since then, many phone manufacturers have launched phones with in-display / under-display sensors. Some high end-devices also included ultrasonic in-display fingerprint sensor for enhanced security and performance.

Mobile devices now offer multiple biometric recognition methods: smart digital assistant using voice recognition as well as face, iris and fingerprint recognition for device security and authentication.

Biometrics’ success on mobile phone encouraged manufacturers of other consumer electronic products to integrate biometric security to replace their existing authentication methods. Smart home security systems, home appliances, smart devices, etc. have already started taking biometric route.

Biometrics, once limited to only a few applications and high-end facilities is now everywhere. It carried the stigma of being a criminal identification method for a very long time, however, now people do not hesitate to present their fingerprints for unlocking phones to authenticating their identity.

Frictionless and secure yet instant identification is the need of the hour, staying stranded at identification or authentication formalities is one of the top time wasters in personal as well as professional space.

The way things are moving, soon we will be living in the world where staying in authenticated state will be a necessity. Fifth generation of cellular mobile communication is knocking door and we are about to enter 5G and IoT era.

IoT will bring along connected vehicles, devices, appliances, home security systems, and much more and these connected systems will have to make sure that only authorized individuals can access them.

We all have experienced the identification and authentication practices taking a shift in recent years and this is just the beginning. Biometrics is here to stay and there is a lot more to come. We will make sure that this article is able to keep up with the latest in the field of biometrics.