Saturday, June 25, 2005

Signature recognition

Signature verification is the process used to recognize an individual’s hand-written signature.

Dynamic signature verification technology uses the behavioral biometrics of a hand written signature to confirm the identity of a computer user. This is done by analyzing the shape, speed, stroke, pen pressure and timing information during the act of signing. Natural and intuitive, the technology is easy to explain and trust.

As a replacement for a password or a PIN number, dynamic signature verification is a biometric technology that is used to positively identify a person from their handwritten signature.

There is an important distinction between simple signature comparisons and dynamic signature verification. Both can be computerized, but a simple comparison only takes into account what the signature looks like. Dynamic signature verification takes into account how the signature was made. With dynamic signature verification it is not the shape or look of the signature that is meaningful, it is the changes in speed, pressure and timing that occur during the act of signing. Only the original signer can recreate the changes in timing and X, Y, and Z (pressure).

A pasted bitmap, a copy machine or an expert forger may be able to duplicate what a signature looks like, but it is virtually impossible to duplicate the timing changes in X, Y and Z (pressure). The practiced and natural motion of the original signer would required to repeat the patterns shown.

There will always be slight variations in a person’s handwritten signature, but the consistency created by natural motion and practice over time creates a recognizable pattern that makes the handwritten signature a natural for biometric identification.

Signature verification is natural and intuitive. The technology is easy to explain and trust. The primary advantage that signature verification systems have over other types of biometric technologies is that signatures are already accepted as the common method of identity verification. This history of trust means that people are very willing to accept a signature based verification system.

Dynamic signature verification technology uses the behavioral biometrics of a hand written signature to confirm the identity of a computer user. Unlike the older technologies of passwords and keycards - which are often shared or easily forgotten, lost, and stolen - dynamic signature verification provides a simple and natural method for increased computer security and trusted document authorization.

Signature-Scan: How It Works

Signature-scan technology utilizes the distinctive aspects of the signature to verify the identity of individuals. The technology examines the behavioral components of the signature, such as stroke order, speed and pressure, as opposed to comparing visual images of signatures. Unlike traditional signature comparison technologies, signature-scan measures the physical activity of signing. While a system may also leverage a comparison of the visual appearance of a signature, or “static signature,” the primary components of signature-scan are behavioral.

The signature, along with the variables present during the signing process, is transmitted to a local PC for template generation. Verification can take place against a local PC or a central PC, depending on the application. In employee-facing signature-scan applications such as purchase order authentication, local processing may be preferred; there may be just a single PC used for such authorization. For customer-facing applications, such as retail or banking authentication, centralized authentication is likely necessary because the user may sign at one of many locations.

The results of signature-scan comparisons must be tied into existing authentication schemes or used as the basis of new authentication procedures. For example, in a transactional authentication scenario, the “authorize transaction” message might be sent after a signature is acquired by a central PC. When signature-scan is integrated into this process, an additional routine requires that the signature characteristics be successfully matched against those on file in order for the “authorize transaction” message to go forward. In other applications, the results of a signature-scan match may simply be noted and appended to a transaction. For example, in document authentication, an unsuccessful comparison may be flagged for future resolution while not halting a transaction. The simplest example would be a signature used for handheld device login: the successful authentication message merely needs to be integrated into the login module, similarly to a PIN or password



Signature-Scan: Strengths and Weaknesses

Signature-Scan has several strengths. Because of the large amount of data present in a signature-scan template, as well as the difficulty in mimicking the behavior of signing, signature scan-technology is highly resistant to imposter attempts. As a result of the low False Acceptance Rates (FAR), a measure of the likelihood that a user claiming a false identity will be accepted, deployers can have a high confidence level that successfully matched users are who they claim to be. Signature-scan also benefits from its ability to leverage existing processes and hardware, such as signature capture tablets and systems based on public key infrastructure (PKI), a popular method for data encryption. Since most people are accustomed to providing their signatures during customer interactions, the technology is considered less invasive than some other biometrics.

However, signature-scan has several weaknesses. Signature-scan 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-scan. During enrollment subjects must provide a series of signatures that are similar enough that the system can locate a large percentages of the common characteristics between the enrollment signatures. During verification enough characteristics must remain constant to determine with confidence that the authorized person signed. As a result, individuals with muscular illnesses and people who sometimes sign with only their initials might result in a higher False Rejection Rate (FRR), which measures the likelihood that a system will incorrectly reject an authorized user. Since many users are unaccustomed to signing on a tablet, some subjects' signatures may differ to their signatures on ink and paper, increasing the potential for false rejection.

Typical Signature-Scan Applications

Signature-scan is implemented in situations where signature or written input processes are already in place. These applications include contract execution, formal agreements, acknowledgement of services received, access to controlled documents, etc.

As the act of signing documents becomes more integrated with electronic capture processes - signing on acquisition tablets, using special styluses, etc. - the opportunity for biometric authentication will increase dramatically. As of today, there are few acquisition devices deployed in operational environments capable of capturing biometric data. Note that signature-scan is not the same as signature capture, currently used in various point-of-sale systems. Nor is it the same as digital signatures, an encryption technology.

Signature-Scan Market Size

Though it is one of the least frequently deployed technology in the biometric market today, signature-scan usage will increase, as a complement to static signature capture, through 2005. Though a handful of vendors sell signature-scan, these firms will need to show the success of the technology in more high-profile settings. As applications for contract execution, formal agreements and access to controlled documents are demonstrated, signature-scan revenues are projected to grow from $3.0m in 2000 to $101.1m in 2005. Signature-scan revenues are expected to comprise approximately 5% of the entire biometric market.





Difference between Biometric and digital signatures

Handwriting has been around since the beginning of civilization and the ‘signature ’or the act of sign-ing a document,has long been accepted by nearly every culture as one ’s recognition and agreement on the contents and implications of written words.

The increasing recognition of electronic signatures by lawmakers is bringing to the forefront concerns over electronic security for privacy and protection of individuals.

For many now conducting business transactions over private networks or the Internet,some form of offcial acknowledgement is now essential and legally binding.The security implications of producing or recognizing ‘original ’electronic documents will be more important than ever before.In this respect, it is important to understand the distinction between the terms “Biometric ” and “Digital ” signatures.

A digital signature is a term used to describe a long numerical code that has been uniquely assigned to one person,hence the reference to ‘signature ’.It has nothing to do with a real signature.Their purpose is to be used in encryption systems.Asymmetric encryption (or PKI)is an example of a popular encryption approach.A digital signature is issued to an individual by what is called a Certificate Authority.This is a group or organization responsible for maintenance and safekeeping of digital signatures.Because of their length no one actually remembers or even knows their digital signature.

An individual ’s digital signature will normally reside on his or her computer,or can be stored on a card (similar to banking cards).When someone wishes to encrypt an electronic document,they will use a password or PIN that in turn allows the digital signature to be used.Although secure once encrypted, digital signatures are only as safe as the medium where they reside.Anyone obtaining access to your password,PIN or computer can potentially make unauthorized use of your digital signature.The use of a digital signature does not guarantee the identity of the originator. Handwriting results from a highly complex series of dynamic neuromuscular tasks from brain to fingertips.A naturally developed signature represents the most often reproduced and habitual act of writing.

Although we never sign exactly the same way twice,the signature adheres within certain boundaries unique to each individual.This natural variation is an essential component of handwriting.It also means that each signature is unique in that no two will be identical in all discrete features.Unlike fingerprints,retinal or DNA patterns which remain constant over time,the execution of a person ’s signature will be unique and individual at that particular moment.Handwriting remains one of the most powerful human identifiers that exist today.Identical twins will have the same DNA pattern while their handwriting and signatures remain distinctively different.

Biometric signature is a term used to refer to a signature that has been recorded/captured using a variety of input devices such as digitizing tablets,personal digital assistants (PDA),computer displays or other contact sensitive technologies.This method allows real handwritten signatures to be incorporated into e-documents during electronic transactions.Not every technology captures signature information the same way.Some systems have a static approach and will only record an image of a signature and as such do not record the unique behavioral elements associated with the execution of a signature.In a biometric system such as CIC ’s SignItÔ,both the geometric and dynamic characteristics of the signing process will be recorded and incorporated in an electronic document.Most of the elements that make a signature unique and identifiable can be derived from the digital signature data.Furthermore,the data that is incorporated in an electronic document can be used to lock and protect the contents from alteration.Biometric signatures can also be used to provide and control access security to buildings,networks,computers,documents and databases.

For the layperson,the pictorial appearance of a conventional signature can be convincingly imitated. Forensically,when there is a question of whether or not the signature on a document is genuine, expert visual and microscopic examination is required.This involves evaluating and comparing the general and discrete features of the contested signature with known signatures.With biometric signatures,the authentication can be done in real-time or after the fact.In the event that a biometric signature is contested,the signature data can be extracted from the document and submitted to similar forensic investigation and analysis to verify the authenticity of the signature.

In fact, some of the biometric data that is captured such as speed,acceleration,deceleration,and the amount of time the pen is on and off the paper is accurately measured.This data is either unavailable or qualitatively assessed at best in conventional forensic examinations of signatures.The additional behavioral features recorded from biometric signatures make them even more difficult if not impossible to imitate.

Biometric signatures represent an ideal bridge between the long-recognized convention of signing a document and the need for electronic documents to be uniquely recognized by individuals.This application provides individuals with security and control on documents originated,transacted and stored in the digital domain.

Iris recognition

Iris scan biometrics employs the unique characteristics and
features of the human iris in order to verify the identity of
an individual. The iris is the area of the eye where the
pigmented or coloured circle, usually brown or blue, rings the
dark pupil of the eye.




The iris-scan process begins with a photograph. A
specialized camera, typically very close to the subject, no
more than three feet, uses an infrared imager to illuminate
the eye and capture a very high-resolution photograph. This
process takes only one to two seconds and provides the details
of the iris that are mapped, recorded and stored for future
matching/verification.


Eyeglasses and contact lenses present no problems to the
quality of the image and the iris-scan systems test for a live
eye by checking for the normal continuous fluctuation in pupil
size.


The inner edge of the iris is located by an iris-scan
algorithm which maps the iris’ distinct patterns and
characteristics. An algorithm is a series of directives that
tell a biometric system how to interpret a specific problem.
Algorithms have a number of steps and are used by the
biometric system to determine if a biometric sample and record
is a match.


Iris’ are composed before birth and, except in the event of
an injury to the eyeball, remain unchanged throughout an
individual’s lifetime. Iris patterns are extremely complex,
carry an astonishing amount of information and have over 200
unique spots. The fact that an individual’s right and left
eyes are different and that patterns are easy to capture,
establishes iris-scan technology as one of the biometrics that
is very resistant to false matching and fraud.


The false acceptance rate for iris recognition systems is 1
in 1.2 million, statistically better than the average
fingerprint recognition system. The real benefit is in the
false-rejection rate, a measure of authenticated users who are
rejected. Fingerprint scanners have a 3 percent
false-rejection rate, whereas iris scanning systems boast
ratees at the 0 percent level.


Iris-scan technology has been piloted in ATM environments
in England, the US, Japan and Germany since as early as 1997.
In these pilots the customer’s iris data became the
verification tool for access to the bank account, thereby
eliminating the need for the customer to enter a PIN number or
password. When the customer presented their eyeball to the ATM
machine and the identity verification was positive, access was
allowed to the bank account. These applications were very
successful and eliminated the concern over forgotten or stolen
passwords and received tremendously high customer approval
ratings.


Airports have begun to use iris-scanning for such diverse
functions as employee identification/verification for movement
through secure areas and allowing registered frequent airline
passengers a system that enables fast and easy identity
verification in order to expedite their path through passport
control.


Other applications include monitoring prison transfers and
releases, as well as projects designed to authenticate on-line
purchasing, on-line banking, on-line voting and on-line stock
trading to name just a few. Iris-scan offers a high level of
user security, privacy and general peace of mind for the
consumer.


A highly accurate technology such as iris-scan has vast
appeal because the inherent argument for any biometric is, of
course, increased security


 


Benefits of Using Iris Technology


 



  • The iris is a thin membrane on the interior of the
    eyeball. Iris patterns are extremely complex.
  • Patterns are individual (even in fraternal or identical
    twins).
  • Patterns are formed by six months after birth, stable
    after a year. They remain the same for life.
  • Imitation is almost impossible.
  • Patterns are easy to capture and encode





face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=3>Technology Comparison













































face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Method
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Coded Pattern
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Misidentification
rate
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Security
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Applications
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Iris Recognition
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Iris pattern
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>1/1,200,000
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>High
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>High-security
facilities
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Fingerprinting
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Fingerprints
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>1/1,000
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Medium
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Universal
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Hand Shape
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Size, length and thickness of
hands
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>1/700
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low-security
facilities
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Facial Recognition
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Outline, shape and distribution of
eyes and nose
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>1/100
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low-security
facilities
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Signature
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Shape of letters, writing order,
pen pressure
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>1/100
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low-security
facilities
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Voiceprinting
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Voice characteristics
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>1/30
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Low
face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=2>Telephone
service





face=Verdana,Arial,Helvetica,Geneva,Swiss,SunSans-Regular
color=#000000 size=3>Source: AIM Japan, Automatic
Identification Seminar, Sept.14,
2001


 


Iris-Scan: How it Works


Dr. John Daugman's work in iris recognition form
the basis of this information. Information and images found on his website,
http://www.cl.cam.ac.uk/users/jgd1000, are presented below. 


Iris recognition leverages the unique features of
the human iris to perform identification and, in certain cases, verification.  






The Iris


Iris recognition is based on visible (via regular
and/or infrared light) qualities of the iris. A primary visible characteristic
is the trabecular meshwork (permanently formed by the 8th month of gestation), a
tissue which gives the appearance of dividing the iris in a radial fashion.
Other visible characteristics include rings, furrows, freckles, and the corona,
to cite only the more familiar.  


IrisCodeTM


Expressed simply, iris recognition technology
converts these visible characteristics as a phase sequence into a 512 byte
IrisCode(tm), a template stored for future identification attempts. From the
iris' 11mm diameter, Dr. Daugman's algorithms provide 3.4 bits of data per
square mm. This density of information is such that each iris can be said to
have 266 'degrees of freedom', as opposed to 13-60 for traditional biometric
technologies. This '266' measurement is cited in most iris recognition
literature; after allowing for the algorithm's correlative functions and for
characteristics inherent to most human eyes, Dr. Daugman concludes that 173
"independent binary degrees-of-freedom" can be extracted from his algorithm - an
exceptionally large number for a biometric. A key differentiator of iris-scan
technology is the fact that 512 byte templates are generated for every iris,
which facilitates match speed (capable of matching over 500,000 templates per
second) 


Iris Acquisition 


The first step is location of the iris by a
dedicated camera no more than 3 feet from the eye. After the camera situates the
eye, the algorithm narrows in from the right and left of the iris to locate its
outer edge. This horizontal approach accounts for obstruction caused by the
eyelids. It simultaneously locates the inner edge of the iris (at the pupil),
excluding the lower 90° because of inherent moisture and lighting issues. 

 


Iris-Scan Issues


Iris-scan technology requires reasonably controlled
and cooperative user interaction - the enrollee must hold still in a certain
spot, even if only momentarily. Many users struggle to interact with the system
until they become accustomed to its operations. In applications whose user
interaction is frequent (e.g. employee physical access), the technology grows
easier to use; however, applications in which user interaction is infrequent
(e.g. national ID) may encounter ease-of-use issues. Over time, with improved
acquisition devices, this issue should grow less problematic. 


The accuracy claims associated with iris-scan
technology may overstate the real-world efficacy of the technology. Because the
claimed equal error rates are derived from assessment and matching of ideal iris
images (unlike those acquired in the field), actual results may not live up to
the astronomical projections provided by leading suppliers of the technology. 


Lastly, since iris technology is designed to be an
identification technology, fallback procedures may not be as fully developed as
in a verification deployment (users accustomed to identification may not carry
necessary ID, for example). Though these issues do not reduce the effectiveness
of iris recognition technology, they must be kept in mind should a company
decide to implement on iris-based solution.


Iris-Scan Applications


Iris-scan technology has traditionally been
deployed in high-security employee-facing physical access implementations,
although 2002 saw a number of novel, high-profile iris-scan deployments in new
applications. Iridian - the technology’s primary developer - is dedicated to
moving the technology to the desktop, and has had some success in small-scale
logical access deployments. The most prominent recent deployments of iris-scan
technology have been passenger authentication programs at airports in the U.S.,
U.K., Amsterdam, and Iceland; the technology is also used in corrections
applications in the U.S. to identify inmates. A number of developing countries
are considering iris-scan technology for national ID and other large-scale 1:N
applications, although to date it is still believed that the largest deployed
Iridian database spans under 100,000 enrollees. Notable iris-scan applications
include the following. 







































































Project Description



Location



Vertical Sector



Horizontal Application



Application Description



Additional Description


Iris
in Pakistan



Pakistan



Government


Civil
ID



Tracking


Afghan
refugees receive assistance package on first enrollment through UNHCR


Iris
Pilot - Logan


US-MA


Travel
and Transportation


Phys
Acc/T&A



Physical Access


Iris
piloted for employee access to security office (LG3000)


JFK
Iris Pilot


US-NY


Travel
and Transportation


Phys
Acc/T&A



Physical Access


1 door
to tarmac protected


City
Hospital of Bad Reichenhall in Bavaria



Germany


Health
care


Phys
Acc/T&A



Physical Access


Access
control to infant center to prevent kidnappings



Singapore Border Crossing



Singapore



Government


Travel
and Transportation



Physical Access


50k
day workers enter Singapore from Malaysia daily by motorcycle. Iris-scan
does 1:N


UK
Passport Office Iris Pilot


UK



Government


Civil
ID



Passport


Opt-in
pilot to test iris acceptance, part of 6-mo public comment period



Venerable Bede (UK) School - Iris


UK



Education



Retail/ATM/POS


POS



900-pupil school to use Iridian for library check-out and cafeteria
payment




 


 


Iris-Scan Market Size


Though it is one of the later emerging technologies
in the biometric market, iris-scan is set to grow substantially through 2007.
Iris-scan offers low false match rates and hands-free operation, and is the only
viable alternative to fingerprint technologies in 1:N applications where a
single record must be located. Iris-scan's resistance to false matches is offset
somewhat by the the level of training required to use the system effectively. As
such, iris-scan will primarily be used in applications that require high levels
of security, although convenience-driven deployments (e.g. Privium) will
continue. Iris-scan revenues are projected to grow from $16.2m in 2002 to
$210.2m in 2007. Iris-scan revenues are expected to comprise approximately 5% of
the entire biometric market.