The term “Biometrics” is derived from “bio” which means life, and “metric”, which means measurement. Biometrics is developing for use in a variety of technologies, including the unique identification and recognition of people. The technology in its current situation is widely used in security and surveillance systems.
Biometrics also has the possibility of converging with other technologies and scientific studies. For example, behavioral biometrics can help improve evolving computer-human interfaces such as voice control, gesture control, and brainwave control for computer devices. Likewise, morphological and biological biometrics can be beneficial in the study of human evolution. Biological biometrics, such as DNA recognition, combined with different medical and biomedical data sets, can aid in the study of genetic diseases and even identify specific racial characteristics.
Behavioral biometrics assists in the study of physical intelligence (kinesthetic-bodily) to improve and advance in sports and military training. Biometric datasets can especially be used in training the right-brain educational system across all eight types of human intelligence. They are: verbal-linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal and naturalistic. Biometric datasets can be useful in early identification of natural talents and improving training in specific areas of human intelligence.
Biometric data is already used by law enforcement, defense and intelligence agencies. India has successfully demonstrated how biometric data combined with demographic data can issue government-controlled identification and AADHAR cards. AADHAR is the world's most extensive biometric identification system in India, which is formally and informally integrated with the banking, financial, income tax, medical and law enforcement systems. There is even a possibility for the government of India to integrate AADHAR data with land bank data to reduce corruption in the form of Benami properties. The government of India has biometric data (retina, fingerprints of all ten fingers and facial data) of more than 1.28 billion Indians, which is formally used for implementing government-controlled social welfare schemes. It can be used for crime control, law enforcement, anti-terrorism, demographic monitoring, identifying illegal immigration from neighboring countries and even tracking illegal financial transactions and money laundering. This can be done by digitizing various public and private services and combining AADHAR (a biometric identity) with various public and private datasets.
Although security and surveillance applications are limited to biometric identification and recognition, biometric data can have many applications when combined with big data (different sets of public and private data), artificial intelligence, machine learning, Internet of Things and computer interfaces. -human.
The first step in biometrics is the collection of biometric data. For this, there are different types of biometric sensors. These sensors are often designed as edge devices, and more sophisticated sensors are controlled by the cloud, involving a high level of encryption. Let's learn about biometric systems, various biometric sensors and their types.
What is a biometric sensor?
Biometric sensors are transducers that convert biometric characteristics into electrical signals. These features include fingerprints, iris, vein pattern, voice, face, DNA, etc., which are detected and scanned according to a software-defined template. The same model is later used for comparison and unique identification/recognition of people. The operation of a sensor can be intrinsically based on the measurement of one or more physical quantities such as light intensity, capacitance, temperature, image, etc. In a security/surveillance system, a biometric sensor is used as identity technology. Together with other traditional access systems, such as PIN codes or passwords, it guarantees accuracy, making the system foolproof. New security systems do not hesitate to rely exclusively on biometric authentication, eliminating the need to remember passwords or carry security tokens.
Types of biometric sensors
Biometrics is broadly divided into three categories as follows.
Biological biometrics: involves biological measurements at the genetic or molecular level, and DNA sequencing is a biological biometric system. Biological biometrics requires sampling DNA from blood or bodily fluids. This cannot be used for security or authentication systems, but has other practical applications such as DNA matching, genetic diseases and microbiological studies.
Morphological biometrics: involves the measurement of physical characteristics and body structures. Security and authentication systems are generally based on one or another morphological biometrics. These include fingerprint mapping, iris scanning, facial recognition, finger geometry recognition, vein recognition, hand geometry, ear recognition, and odor recognition.
Fingerprint scanning provides secure access with biometric identification
Behavioral biometrics: involves measuring a person's unique behavioral identifiers. These systems are not common, but are reserved for special applications. These include signature recognition, voice biometrics, gait biometrics, keystroke recognition, and gesture recognition.
Biometrics for security and surveillance systems
Security systems use biometrics for authentication, while surveillance systems use biometrics for identification. Security systems often have biometric reference data stored locally, i.e. on the edge device, or the device may not be connected to any internet network. The data may contain models stored to identify different people. When a person requests access, a new sample of biometric data is collected by the scanner and compared with stored templates to determine whether the person is authorized or not. Optical fingerprint scanners are the most widely used biometric security systems. They are low cost and have applications ranging from standalone embedded devices to smartphones and computers. Multispectral fingerprint scanners are better than optical scanners, but they are more expensive. More sophisticated biometric security systems may involve additional measurements such as iris scanning, facial recognition, finger geometry, hand geometry, or vein pattern recognition. Iris scanning along with hand geometry are the most preferred high security systems.
Surveillance systems are intended for identification. Facial recognition is the most viable surveillance system and these systems generally do not have direct interaction or interface with people to be identified. Biometric surveillance systems are always cloud-based, with biometric data sent cryptographically by edge devices over the network.
How do biometric security sensors work?
A biometric security system is designed for authentication. It involves three main steps – registration, storage and comparison. Upon enrollment, valid users' biometric data is entered into the device along with an identification key or number. For example, a fingerprint sensor can collect a valid user's fingerprint template and assign it a unique identification number. This biometric data is stored in memory according to a software-defined template either locally or in a centralized database. With the biometric identity of valid users stored on the device, whenever a user attempts to access the system, a new biometric sample is collected by the biometric scanner and compared with the stored templates. Matching against stored templates determines whether the user's identity is rejected or validated.
Many biometric security systems take a different approach. Biometric data is stored on a smart card rather than on a local device or centralized server. The security system is designed to validate the biometric data stored in the security token with the live sample collected from its user.
Biometric measurements
There are three types of biometric measurements – biological, morphological and behavioral. Different biometric measurements are discussed below.
Biological identifiers:
DNA recognition: involves collecting DNA samples in the form of blood or bodily fluids. DNA is sequenced and stored in a similar format. A person's DNA corresponds to 99.7% of their biological parents and the remaining 0.3% is a variable repetitive code. The redundant code is unique to a person and is used for genetic fingerprinting.
Morphological identifiers:
Facial recognition: involves capturing a digital image of the face through photos, videos or real-time broadcasts. The digital image is compared to a facial recognition standard which is a mapping of various facial features.
Fingerprint Mapping: Fingerprints are unique identifiers. Fingerprints are scanned using optical, ultrasonic or capacitive scanners and stored in a predefined template. The new scans are compared to already stored fingerprint IDs to match an identity.
Finger Geometry Recognition: In this system, the length, width, area and thickness of the finger are used as unique identifiers.
Hand geometry: uses physical characteristics of the entire palm, including characteristics of the fingers, to identify a person.
Retinal Recognition: The pattern of retinal blood vessels is unique to a person. The iris is scanned using visible or infrared light, and retinal patterns are stored according to software-defined markers. The new scans are then compared to the stored retinal pattern for authentication or biometric identification.
Hearing recognition: uses the structure of the ear as an identifier. The shape and structure of the ears remain intact for years and are again a unique feature of the body.
Vein recognition: Veins in the palm, fingers or eyes are scanned using optical scanners, and the vein pattern is stored as a unique identifier.
Odor recognition: involves recognizing scents using unique chemical patterns.
Later recognition: This is a developing technology that measures a person's contour and the pressure point on a chair for unique identification. It is under development as anti-theft technology for automobiles.
Behavioral identifiers:
Signature recognition: involves identifying the handwriting in signatures. This technology is widely used for authentication in banking and financial transactions.
Voice recognition: Uses a person's voice pattern as a unique identifier.
Gait recognition: involves extracting gait features for identification.
How gesture control works. (Image: Aptiv)
Gesture recognition: involves identifying gesture patterns for personal identification.
Keystroke recognition: This involves measuring a person's keystroke and keystroke patterns on a keyboard and using it for identification.
Social Media Engagement Recognition: This cybersecurity system attempts to identify a registered user online based on their previous interaction and engagement with a website.
Advantages and disadvantages of biometrics
Biometric identification systems have several advantages. They are unique to a person and do not change throughout life. These are non-transferable and almost impossible to forge or impersonate. It is also not easy to steal biometric data. Therefore, biometric security systems are more reliable and efficient. There are some cons too. Biometric security systems often require more expensive infrastructure. Biometric data stored locally or on a centralized server can still be hacked, even if it is not easily impersonated or falsified. Biometric systems don't work if they don't receive enough data. Even if biometric identities are stored properly, there are still rare but some chances of false positives and false negatives.
Applications of biometrics
Currently, biometrics is widely used in forensic medicine, law enforcement, airport security, healthcare, military and intelligence, civil identification, civil security, immigration control, access and authentication, banking, financial transaction authentication, peer-to-peer sales and anti-theft technologies. Biometric data has even greater reach when combined with other useful data sets.
Challenges in biometrics
Biometric scanners are integrated into embedded devices as well as smartphones and many consumer devices. Many biometric identification systems such as facial recognition, voice recognition and gesture recognition can be easily implemented online without any specific infrastructure. The growing presence of biometric scanners, surveillance cameras and their connectivity to online networks has raised concerns about data security, privacy breach, identity protection and device security.
Conclusion
Biometric sensors are gaining ground, especially in security and surveillance systems. They are at least more reliable and efficient than traditional password or PIN-based security systems. In addition to security applications, biometric data has its reach when combined with sets of demographic, geographic, medical, scientific, financial and economic data.