TYPES OF BIOMETRIC TECHNOLOGY
In biometry, there
are two types of biometric methods.One is called behavioral biometrics. It is
used for verification purposes. Verification is determining if a person is who
they say they are. This method looks at patterns of how certain activities are
performed by an individual.
Physical
biometrics is the other type used for identification or verification purposes.
Identification refers to determining who a person is. This method is commonly
used in criminal investigations.
4.1Biometrics Based On Physical Character
4.1.1
Fingerprint/
Palmprint Identification or Recognition
This type of biometrics compares two fingerprints to
determine identification. It analyzes the ridges and valleys patterns on the
fingertip for differences. These fingerprint patterns include the arch, loop,
and whorl. In biometric forensics, fingerprint identification is useful for
narrowing down suspects. Some laptop computers utilize fingerprint biometrics
for authorizations for such purposes as logging in and entering website
password.
4.1.2
Face Recognition
Facial
recognition technology utilizes image or
video in order to compare facial features from the chosen source to cataloged
entries in a database. The technology works by creating a virtual grid and
outlining the distance between defining characteristics on the face, as well as
detailed information on the shape of the face: such as the contour of the
nostrils, eyes, and even analyzing the texture of the skin.The technology was
initially pioneered by Woody Bledsoe, Helen Chan Wolf, and Charles Bisson in
1964 as part of their collective study on pattern recognition intelligence
(PRI). After Bledsoe left the study of PRI, the research was continued at
Stanford Research Institute by Peter Hart. In experiments performed using the
collective work of the initial pioneers, as well as his own, the first major
breakthrough happened in 1968 when a computer consistently outperformed humans
in identifying human faces from a database of 2,000 photos.In 1997, Christoph
von der Malsburg as well as a team of graduate students from the University of
Bochum in Germany developed a system known as ZN-Face that was (at the time)
the most robust of its kind due to its ability to make facial matches on
imperfect images. The technology was funded by the United States Army Research
Laboratory and is used by customers ranging from major international airports,
to banks and government offices. Current facial recognition technologies rely
on cross-referencing characteristics of several different facial recognition
technologies and algorithms, and are said to be so powerful that they can
not only significantly outperform humans, but also correctly identify the
individual faces of identical twins. Variations of this technology are
currently being used in consumer grade applications, such as the Xbox One. Using
Kinect Sign-In, users can sign in to their Xbox profile after the Kinect
scans their face and body profile in order to make a positive identification.
The facial scanner is impressive, and even works in rooms full of others where
it has to pick your profile from a group.
4.1.3
Eye Recognition (retina
/ iris)
Retina scanning was the first
ocular biometric technology used, but the technology has since been replaced by
the iris scan, the more advanced – and reliable – of the two technologies. Iris
recognition technology is an
automated identification system that uses mathematical pattern recognition to
map the complex patterns of an individual’s eye. When viewed up close, the iris
displays a network of random patterns which look like a series of woven fibers
and are unique to each individual. The scanners attempts to match these
patterns to a database using images or video representation of the individual’s
eye.
Although the modern technology
surrounding iris scanning and recognition is rather new, the science behind the
technology (iridology) dates back to ancient Egypt and Greece, and even
appeared in the writings of Hippocrates. The modern pioneer of the technology
is John Daugman, who developed and patented the first algorithms for
computer-aided identification of iris patterns in 1994. Although the algorithms
and tech – such as scanners and the means to catalog and retrieve samples – has
improved since this time, Daugman’s algorithms are still the foundation behind
all public deployment of iris recognition technology.
In addition to the physiological
identification methods mentioned above, biometrics specialists have fairly
recently discovered behavioral markers that help to distinguish one human from
another. These methods are known as behavioral biometrics, or behaviometrics.
While the technologies behind these biometric identifiers is still in
development, the commonly held belief is that they aren’t as reliable as
physiological methods. As such, the science behind behavioral biometrics is
still being studied, and breakthroughs could lead to an additional class of
stand-alone biometric identification technologies, or at least an additional
layer in which to cross-reference for added statistical accuracy.
Iris recognition has been,
until recently, a relatively expensive technology that sort of priced its way
out of consumer applications. That could be changing soon, as technologies like Eye Lock – a device used to lock down your
home computer with its own iris scanner – start to come to market.
Fig:-4
(man using eye scanner for Authentication)
4.1.4 DNA
Matching :-
Humans
have 23 pairs of chromosomes containing their DNA blueprint. One member of each
chromosomal pair comes from their mother, the other comes from their father.
Every cell in a human body contains a copy of this DNA. The large majority of
DNA does not differ from person to person, but 0.10 percent of a person’s
entire genome would be unique to each individual. This represents 3 million
base pairs of DNA.
Genes
make up 5 percent of the human genome. The other 95 percent are non-coding
sequences, (which used to be called junk DNA). In non-coding regions there are
identical repeat sequences of DNA, which can be repeated anywhere from one to
30 times in a row. These regions are called variable number tandem repeats
(VNTRs). The number of tandem repeats at specific places (called loci) on
chromosomes varies between individuals. For any given VNTR loci in an
individual’s DNA, there will be a certain number of repeats. The higher number
of loci are analysed, the smaller the probability to find two unrelated individuals
with the same DNA profile.
DNA
profiling determines the number of VNTR repeats at a number of distinctive
loci, and use it to create an individual’s DNA profile. The main steps to
create a DNA profile are: isolate the DNA (from a sample such as blood, saliva,
hair, semen, or tissue), cut the DNA up into shorter fragments containing known
VNTR areas, sort the DNA fragments by size, and compare the DNA fragments in
different samples.It is very Accurate that the chance
of 2 individuals sharing the same DNA profile is less than one in a hundred
billion with 26 different bands studied.
4.2Biometrics
Based on Behavioral Character
Behavioral biometrics is the field of study
related to the measure of uniquely identifying and measurable patterns in human
activities.
4.2.1
Voice Recognition
Speaker
recognition uses the acoustic features of speech that have been found to differ
between individuals. These acoustic patterns reflect both anatomy and learned
behavioral patterns . This incorporation of learned patterns into the voice
templates has earned speaker recognition its classification as a “behavioral
biometric.” Speaker recognition systems employ three styles of spoken input:
text-dependent, text-prompted and text independent.
Most speaker verification
applications use text-dependent input, which involves selection and
enrollment of one or more
voice passwords. Text-prompted input is used whenever there is
concern of imposters. The
various technologies used to process and store voiceprints include
hidden Markov models,
pattern matching algorithms, neural networks, matrix representation
and decision trees.
4.2.2Signature Verification
This
technology uses the dynamic analysis of a signature to authenticate
a person.
The technology is based on measuring speed, pressure and angle used by the
person
when a
signature is produced. One focus for this technology has been e-business
applications
and other
applications where signature is an accepted method of personal authentication.
4.2.3 Typing Rhythm
This
method which is under development is based on the typing characteristics of the
individuals such as
keystroke
duration, inter-keystroke times, typing error frequency, force keystrokes etc.
Two kinds of systems are getting developed based upon
static and dynamic verification techniques The static verifier uses a neural
network approach while the dynamic verifier is using statistics. The static
approach is where the system analyzes the way a username or password was typed
using neural network for pattern recognition. Dynamic approach is where the
system verifies the person continuously with any arbitrary text
input.
This is a method that can be offered as supplement to
some secure authentication mechanism and not to be used independently. The
performance of the method is affected by various circumstances of the human
users, such as a hand injury or fatigue of the
legitimate user. The systems developed for this biometric
method are costly since they use neurological methods
and dedicated terminals. Products under development for keystroke dynamics will
come from BioPassword Security Systems, UK, Electronic Signature Lock
Marketing, U.S.A., M&T Technologies U.S.A.
5
Some Developing Biometrics
5.1 DNA Pattern
This method takes advantage of the different
biological pattern of the DNA molecule between individuals.Unique differences
in the banding pattern of the DNA fragments occur. DNA prints were first used
in 1983 in United Kingdom.
5.2 Sweat Pores Analysis
The distribution of the pores in the area of the
finger is distinct for each individual. Based on this observation sweat pores
analyzers have been developed which analyze the sweat pores on the tip of the
finger. When the finger is placed on the sensor, the software records the pores
as stars and stores their position relative to the area of the finger. A system
under development is: PCMCIA (Personal Biometric Encoders, U.K.)
(a real fingerprint and artificial fingerprint that is
not recognized by fingerprint scanner)
5.3 Ear Recognition
The
shape, size of the ears are unique characteristics of an individual. This
technique is used in police in
order to
identify criminals.
Product:
Optophone Ear Shape Verifier (ART Techniques, U.S.A.) .In future(soon) ,we will
have a device that scan our ear to recognize us.
Fig-10(man using mobile that uses ear recognition
tech.)
5.4 Odor Detection
The
premise of this technique is that chemicals called rolatiles makes the
distinctive person's smell. A
number of sensors are checking the different compounds
that makes someone's smell. This method is under development. A system that is
suppose to be completed in 1997 is Scentinel (Mastiff Electronics, U.K).
It is concluded that no particular biometric technique
is utilized in an application e.g. access control is using hand analysis and
speech analysis. No single biometric has dominated the market, the market is
open and especially in Eastern European, Ex-Soviet Union countries and any
other country where no identification technologies are used.
5.5 3D Face Recognition
Three-dimensional face recognition (3D face
recognition) is a modality of facial recognition methods in which
the three-dimensional geometry of the human face is used. It has been shown
that 3D face recognition methods can achieve significantly higher accuracy than
their 2D counterparts, rivaling fingerprint recognition.
3D
face recognition has the potential to achieve better accuracy than its 2D
counterpart by measuring geometry of rigid features on the face. This avoids
such pitfalls of 2D face recognition algorithms as change in lighting, different
facial expressions, make-up and head orientation. Another
approach is to use the 3D model to improve accuracy of traditional image based
recognition by transforming the head into a known view. Additionally, most 3D scanners acquire both a 3D mesh and the
corresponding texture. This allows combining the output of pure 3D matchers
with the more traditional 2D face recognition algorithms, thus yielding better
performance (as shown in FRVT
2006).
The
main technological limitation of 3D face recognition methods is the acquisition
of 3D image, which usually requires a range
camera. Alternatively, multiple images from different angles from a common
camera (e.g. webcam) may be used to create the 3D model with significant
post-processing. This
is also a reason why 3D face recognition methods have emerged significantly
later (in the late 1980s) than 2D methods. Recently commercial solutions have
implemented depth perception by projecting a grid onto the face and integrating
video capture of it into a high resolution 3D model. This allows for good
recognition accuracy with low cost off-the-shelf components.
3D
face recognition is still an active research field, though several vendors
offer commercial solutions.
5.6 EAR REcognition
6. Applications
of Biometrics Technology
Iris-based
identification and verification technology has gained acceptance in a number of
different areas. Application of iris recognition technology can he limited only
by imagination. The important applications are those following:--
·
Used in ATM’s for more
secure transaction.
·
Used in airports for
security purposes.
·
Computer login: The
iris as a living password
·
Credit-card
authentication
·
Secure financial
transaction (e-commerce, banking).
·
“Biometric—key
Cryptography “for encrypting/decrypting messages.
·
Driving licenses and
other personal certificates.
·
Entitlements and
benefits authentication.
·
Forensics, birth
certificates, tracking missing or wanted person
7. Some
Limitations Of Biometrics
1. High Cost
In comparison to ID cards in the workplace, biometric devices are much more
costly. Biometric technology is much more effective for security and
identification purposes, but it is also much more expensive. Many biometric
devices are not cheap and come with a high price.
2. Errors Can Occur
Even though biometric technology is known to be very effective and reliable,
this does not mean that errors are nonexistent. The error rate for most
biometric devices is around 1%, which is small but there is still a small
chance of error. This means that if 1,000 people are identified using biometric
technology about 10 will be misidentified. This is a small number, but it is an
issue. Wrongly identifying someone can lead to major problems depending on the
setting that the biometric device is used in. Eliminating errors altogether in
identifying people using biometric technology is not possible.
3. Criminals Can Get Around
Biometric Devices
It is possible for criminals to find ways to get around biometric technology.
This means that biometric devices are not completely effective in halting
criminals. Under certain lighting and in certain temperatures, biometric
devices are even impaired further.
4. In fingerprint recognition It can make mistakes with the
dryness or dirty of the finger’s skin, as well as with the age (is not
appropriate with children, because the size of their fingerprint changes
quickly).
5. Signature verification is designed to verify subjects based
on the traits of their unique signature. As a result, individuals who do not
sign their names in a consistent manner may have difficulty enrolling and
verifying in signature verification.
·
Conclusion
Biometrics is a viable replacement for, or
enhancement to, the use of passwords or PINs to verify the identity of a
person. Each person’s characteristics are unique to that individual. Even
identical twins do not have the exact same characteristics. Also keep in mind
that it is very hard to lose, and impossible to forget your personal
characteristics, since they are a physical part of you. The use of biometrics
will significantly increase the probability that the person accessing the
information is actually the person they say they are. Biometric systems are used increasingly to recognize individuals and
regulate access to physical spaces, information, services, and to other rights
or benefits, including the ability to cross international borders. The motivations
for using biometrics are diverse and often overlap. They include improving the
convenience and efficiency of routine access transactions, reducing fraud, and
enhancing public safety and national security. Questions persist, however,
about the effectiveness of biometric systems as security or surveillance
mechanisms, their usability and manageability, appropriateness in widely
varying contexts, social impacts, effects on privacy, and legal and policy
implications.
References From:-
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