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iGuard Terminology |
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Biometrics
The automatic recognition of
persons based on unique combinations of
measurable physical or behavioral
characteristics. Examples include
fingerprints, iris scanning, face and
voice recognition, or hand geometry. All
of these biometric techniques are
differentiated by speed, durability,
reliability, and cost effectiveness.
Fingerprints are generally considered
the most practical biometric identifier
in use today. The iGuard Security
Network Appliances use Fingerprint
technology.
Biometric Authentication Method
(Mode)
The way biometric data (e.g.
fingerprints) is used for
authentication. The mode chosen for a
biometric installation depends on the
specific needs of a site, where either
convenience or security may be
emphasized.
Verification
Also known as 1:1 This type
of biometric credential management
system utilizes a secondary "statement
of user identity". In other words, you
must also authenticate yourself by
something you possess or know and not
just by something you are. An example
her is when I walk up to my PC I insert
my smart card (something I have) into a
SC reader attached to my fingerprint
scanner or input my PIN or password
(something I know) and then authenticate
biometrically using my finger on the
scanner. The program asks:
Is this person
whom they claim to be? This
type of credential management system is
the fastest template matching method and
is the most secure authentication method
available today.
Identification
Also known as one-to-many or
1:n comparison. This type of biometric
credential management relies solely upon
the biometric credential as the
statement of user identity. As an
example, when I place my finger upon the
biometric reader, the program looks at
the presented template and goes to the
template warehouse and attempts to
identify my fingerprint from the entire
database. The program asks:
Who is this
person? Then it asks: Does
this person have access? Then the
program grants or denies access based
upon the business rules previously
assigned. This is the slowest form of
authentication and is also the most open
to the types of errors detailed above.
Authorization
The administration of
person-specific rights, privileges, or
access to data or corporate resources.
Authentication
Any systematic method of
confirming the identity of an
individual. Some methods are more secure
than others. Simple authentication
methods include user name and password,
while more secure methods include
token-based one-time passwords. The most
secure authentication methods include
layered or "multi-factor biometric
procedures. This is independent of
authorization.
False
Acceptance Rate
Also known as FAR. False
Acceptance Rate - This is the rate at
which a device will accept false
biometric credentials as acceptable.
This level of error is extremely rare,
and usually falls within the 1 in
1,000,000 or better range. An example of
this type of error: Ben is not
authenticated to access his corporate
network via biometric authentication.
His fingerprint on his right index
finger is close enough to Mary's that he
is able to authenticate access by using
her identity. He is granted access even
though he doesn't possess valid
biometric credentials. The odds of this
happening in reality with 16 minutiae
points captured is quite literally 1 in
a Million.
False
Rejection Rate
Also known as FRR. False
Rejection Rate - This is the rate at
which a device will deny access based
upon misreading or misidentifying
genuine biometric credentials as
"false". An example of this type of
error: Mary is authorized to access her
facility by authenticating her
fingerprint on a fingerprint reader at
the door. Today, while trying to enter
the facility, Mary didn't have her
finger properly centered on the device,
so the minutiae points captured and
compared during this attempt are notably
different than what is on the stored
template. She is denied access even
though she has a valid biometric
credential (her finger). This is the
most common type of error and most
devices will default to a FRR as opposed
to FAR if the templates are noticeably
different.
Latent
Fingerprint
Latent fingerprints are "left
over" fragments usually caused by the
build-up of oily residues on the optic
sensor window after repeated use. The
Verification technique used
by iGuard devices to defeat "faked"
fingerprints also prevents latent
fingerprints from being incorrectly
validated by the system.
Matching
Biometric data (e.g.
fingerprints) are matched to another
sample to confirm a person’s identity
(authentication). For example, BioCert
biometric systems use optic scanners to
collect fingerprint minutiae, then
create mathematical templates based on
that information for storage. New input
fingerprints are scanned and compared to
the stored samples. If the minutiae
matching threshold is met, the person is
authenticated.
Minutiae
The unique, measurable
physical characteristics scanned as
input and stored for matching by
biometric systems. For fingerprints,
minutiae include the starting and ending
points of ridges, and ridge junctions
among other features.
Biometric
Template
The biometric reference
pattern of a person stored for matching.
BioCert devices convert fingerprint
minutiae into mathematical templates, so
actual fingerprint images are not stored
and cannot be reconstructed based on
template data.
Master/Slave
Units
The terms Master/Slave have been
used for years in the computer industry
to describe devices that are dependent
upon a connection to each other. A
slave device receives instructions and
data from the master unit and replicates
all fingerprint and access privileges
from the master unit. In this
configuration, you can control and query
multiple iGuard units from a single web
interface on the master device.
Once you set privileges and access
rights, each slave unit will accept
these instructions and carry them out
even if the devices are disconnected
from the network. Each iGuard can
store up to 4000 transactions and once
the connection to the network is
restored, each slave unit will upload
the transaction data to the master
device.
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