Balancing Privacy, Security and Convenience with Biometrics

BIOMETRICS IN THE UNITED STATES: BALANCING
PRIVACY, SECURITY,
AND ACCESSIBILITY
A Master Thesis
Submitted to the Faculty
of
American Military University
by
YOUR NAME
In Partial Fulfillment of the
Requirements for the Degree
of
Master of Science
May 2014
American Military University
Charles Town, WV

BIOMETRICS IN THE UNITED STATES ii
The author hereby grants the American Public University
System the right to display these
contents for educational purposes.
The author assumes total responsibility for meeting the
requirements set by United States
copyright law for the inclusion of any materials that are not the
author’s creation or in the public
domain.

© Copyright 2014 by Joshua Dale Brandt
All rights reserved.
BIOMETRICS IN THE UNITED STATES iii
DEDICATION
I dedicate this thesis to my parents, wife, and dogs. I could not
have completed this work
without their patience, understanding, support, and
encouragement. I owe all of them some time
and attention that has been deferred while I have worked on this
study.

BIOMETRICS IN THE UNITED STATES iv
ACKNOWLEDGMENTS
XXXX
BIOMETRICS IN THE UNITED STATES v
ABSTRACT OF THE THESIS
BIOMETRICS IN THE UNITED STATES: BALANCING
PRIVACY, SECURITY, AND
ACCESSIBILITY

by
NAME
American Military University, May 2014
Charles Town, West Virginia
Dr. Novadean Watson-Stone, Thesis Professor
Biometrics technology has the potential to improve security,
protect privacy, and increase
accessibility. However, the technology has not been utilized to
its full potential. This paper will
review existing literature and past studies to highlight existing
biometrics, biometrics usage,
privacy concerns, and actions that can be taken to mitigate those
concerns. The purpose of this
literature review is to identify potential uses for biometrics in
the United States and steps that can
be taken to implement that technology. Additionally, this paper

will discuss a study conducted
to determine the current attitudes of American citizens towards
biometrics. The study was
conducted electronically using both quantitative and qualitative
methodology and determined
that there are several factors that influence acceptance of
biometrics by Americans including the
security of the information, the age of the participant, and the
education level of the individual.
The study also determined that Americans are generally
accepting of biometrics use, but there
are some concerns about the technology, how it is used, and its
accuracy.
Keywords: biometrics, privacy, security, accessibility,
technology acceptance
BIOMETRICS IN THE UNITED STATES vi
TABLE OF CONTENTS
COPYRIGHT PAGE
…………………………………………………………………………
….. ii
DECLARATION
…………………………………………………………………………

……... iii
ACKNOWLEDGMENTS
……………………………………………………………………….
iv
ABSTRACT
…………………………………………………………………………
…………… v
TABLE OF CONTENTS
………………………………………………………………………...
vi
LIST OF TABLES
…………………………………………………………………………
……. ix
LIST OF FIGURES
…………………………………………………………………………
…… x
CHAPTER
I. I
INTRODUCTION……………..……………………………………
……………………. 1
Problem Statement
………………………………………………………………………. 2
Purpose
…………………………………………………………………………

………… 2
Hypotheses
…………………………………………………………………………
…….. 2
Significance of the Study
………………………………………………………………... 3
II. L
LITERATURE
REVIEW…………..…………………………………………………
….. 5
Biometrics Overview, Modalities, & Accuracy
...……………………………………….. 5
Current Biometrics Uses in United States and Abroad
....………………………………. 10
BIOMETRICS IN THE UNITED STATES vii
Previous Surveys
………………………………………………………………………...
15
Concerns About Biometrics
……………………………………………………………. 21
Mitigating Measures to Address Concerns
…………………………...………………… 25

Actions to Improve Acceptance
………………………………………………………... 27
Remaining Questions
…………………………………………………………………… 29
III. M
METHODOLOGY……………………………………………………
………………… 31
Data Collection Technique
……………………………………………………………... 31
Subjects and Setting
…………………………………………………………………….. 33
Statistical Analysis
………………………………………………………………………
34
Limitations of the Study
…………………………………………………………………34
IV. R
RESULTS……………………………………………………………
………………….. 37
Demographics and Response Distribution
……………………………………………… 37
Impact of Education
…………………………………………………………………...... 44

Impact of Different Modalities
…………………………………………………………. 45
Impact of Gender and Age
……………………………………………………………… 46
Impact of Experience with Biometrics
.………………………………………………… 47
Impact of Employment Status
………………………………………………………….. 49
BIOMETRICS IN THE UNITED STATES viii
V. D
DISCUSSION AND CONCLUSION
.…………………………………………………. 51
VI. S
SUMMARY
…………………………………………………………………………
….. 58
VII. R
RECOMMENDATIONS
……………………………………………………………….. 60

LIST OF
REFERENCES………………………………………………………
………………... 61
APPENDICES………………………………………………………
…………………………... 67
Appendix A: Survey
Questions…………………………………………………………. 67
Appendix B: Survey Summary
…………………………………………………………. 74
BIOMETRICS IN THE UNITED STATES ix
LIST OF TABLES
TABLE PAGE
1. Number of Participants by Demographic
…...……………………………………………….. 38
2. Quantitative Questions
………………….……………………………………………………
41

BIOMETRICS IN THE UNITED STATES x
LIST OF FIGURES
FIGURE PAGE
1. Gender Distribution of the Sample Population
……………………………………………… 39
2. Age Distribution of the Sample Population
…………………………………………………. 39
3. Education Distribution of the Sample Population
…………………………………………… 39
4. Employment Distribution of the Sample Population
………………………………………… 39
5. Experience Distribution of the Sample Population
………………………………………….. 40
6. Response Distribution by Question
………………………………………………………….. 40
7. Qualitative Question #1 Responses
…………………………………………………………. 42
…………………………………………………………. 42
………………………………………………………….. 43

………………………………………………………… 44
11. Impact of Education on Biometrics Acceptance
…………………………………………… 45
12. Impact of Gender on Biometrics Acceptance
……………………………………………… 47
13. Impact of Age on Biometrics Acceptance
…………………………………………………. 47
14. Impact of Experience on Biometrics Acceptance
………………………………………….. 49
15. Impact of Employment Status on Biometrics Acceptance
…………………………………. 50
BIOMETRICS IN THE UNITED STATES 1
Biometrics in the United States: Balancing Privacy, Security,
and Accessibility
Introduction
Biometrics can be defined as either a characteristic or a process.
When used as a
characteristic, biometrics is a measurable physical or behavioral
characteristic that can be used
for automated recognition and when used as a process, it is the
automated method of identifying

an individual based on those characteristics (National Science
and Technology Council, 2006a).
At the very basic understanding, biometric technology can be
used to either authenticate an
individual or identify an individual. This can be achieved
through a one-to-one authentication
where the individual’s biometric identifiers are compared to the
biometrics stored on an
identification document or database for that individual or
through a one-to-many authentication
where the biometric identifiers from the individual are
compared to many biometrics in order to
identify the individual from a biometric match (LeHong & Fenn,
2013). Biometrics, including
fingerprints, iris, facial recognition, gait analysis, voice
analysis and many other measurable
physical and behavioral characteristics, can be used for many
purposes to include authenticating
an identity, enhancing security, identifying terrorists and
criminals, and enabling convenience
features such as reducing requirements for passwords
(“Biometrics researchers aim,” 2013).
While biometrics technology is used in some companies and
fields, its use is not

widespread throughout the United States and it is not being used
to its full potential. The
technology has the ability to positively impact security and
protect the privacy interests of the
citizens of the United States as well as to improve the quality of
life through reducing fraud,
expediting screening processes, and eliminating the need to
carry identification documents. This
paper intends to prove that the benefit of biometrics technology
has no impact on its acceptance
by United States citizens. It also seeks to prove that greater
socialization during development of
biometrics technology will lead to greater acceptance of the
technology.
Problem Statement
While the potential for biometrics information to be misused by
the government or
commercial organizations exist, the benefits outweigh the risks.
Biometrics can be used to
balance privacy, security, and accessibility by accurately
verifying the identity of an individual,

minimizing the potential of fraud, and possibly eliminating the
need for identification documents
and passwords. This study is designed to identify the types of
biometric technologies that can be
used to achieve that balance and in what conditions American
citizens find their use acceptable.
Purpose
The goal of this study is to analyze data gathered on different
modalities of biometric
technology, its use, and the opinions of American citizens
regarding the technology to identify
areas and situations where biometric technology can be used,
conditions that must be met, and
steps that can be taken to mitigate the concerns and gain the
trust of American citizens. This
paper will evaluate current uses of biometric technology in the
United States and elsewhere to
determine potential uses of biometric technology in the future.
This paper will discuss the
characteristics of different biometric modalities, their accuracy
rates, and the level of
invasiveness associated with them. Combined with the data and
opinions gathered from survey
participants, this study seeks to understand the limitations of

the technology and acceptable use
by the American public to identify viable uses of biometric
technology in the United States to
achieve a balance of privacy concerns, security, accessibility,
and convenience.
Hypotheses or Research Questions
The study intends to prove or disprove nine hypotheses. These
hypotheses will be
evaluated through the results of the literature review and the
survey.
H1. There is no statistically significant evidence that the trust
that personal information
will be protected impacts the acceptance of biometric
technology.
H2. There is no statistically significant evidence that the act of
socialization and public
consultation prior to implementation impacts the acceptance of
biometric technology.
H3. There is no statistically significant evidence that the age of
an individual has an
impact on the acceptance of biometric technology.

H4. There is no statistically significant evidence that desirable
convenience features, such
as the elimination of the need for passwords or expedited
security screening, have an impact on
the acceptance of biometric technology.
H5. There is no statistically significant evidence that the use of
biometrics impacts
American citizens’ perception of security.
H6. There is no statistically significant evidence that the
increase in the level of security
impacts acceptance of biometric technology.
H7. There is no statistically significant evidence that the level
of education obtained by
an individual impacts acceptance of biometric technology.
H8. There is no statistically significant evidence that an
individual’s gender impacts
acceptance of biometric technology.
H9. There is no statistically significant evidence that the use of
different biometric
modalities impacts acceptance of biometric technology.
Significance of the Study

This study intends to advance the understanding of the
American citizen’s opinions of
biometric technology and its use in the United States. It will
identify variables and will use the
information to identify areas and situations where biometric
technology can be used successfully.
This study intends to also identify measures that can be taken to
ensure that biometric technology
is successfully deployed with suitable acceptance by American
citizens. The results of this study
may be adapted by manufacturers of biometric technology and
may be incorporated into policy
governing the use of biometric technology by state, federal, and
private organizations.
Additionally, the results of this study may be used to adapt
biometric technology to appeal to
more people and may also be used to develop an educational
campaign to promote understanding
and acceptance of the technology and its use.
This study will include literature reviews of the existing
material available on biometrics

to include different modalities and their accuracy rates, current
uses for biometrics, privacy
concerns, and measures that can be taken to reduce any
concerns about biometrics use.
Additionally, this study will discuss the research methodology
used including a summary of the
subjects used and the data collection techniques used. Then,
the paper will include analysis of a
survey administered to identify any factors impacting
acceptance of biometrics, potential new
uses of biometrics, and steps that manufacturers can take to
improve their biometrics technology.
Finally, the paper will summarize the information gathered from
the literature review and
research to develop conclusions and recommendations on the
use of biometrics.
Literature Review
Biometrics Overview, Modalities, and Accuracy
Biometrics is a term that comes from the Greek words “bios”
and “metricos” which
means “life measure” (Biruntha, Dhanalakshmi, & Karthik,

2012). It can be used
interchangeably to describe a number of things. Biometrics can
refer to a physical or behavioral
characteristic, to a process, or to a technology (Jefferson,
2010). When used to refer to a
characteristic, the National Science and Technology Council
(NSTC) Subcommittee on
Biometrics defines biometrics as, “A measurable biological
(anatomical and physiological) and
behavioral characteristic that can be used for automated
recognition” (National Science and
Technology Council, 2006a, p.4). The NSTC Biometrics
Glossary defines biometrics as a
process as, “Automated methods of recognizing an individual
based on measurable biological
(anatomical and physiological) and behavioral characteristics”
(p.4). As a technology,
biometrics can be the sensor used to capture the unique physical
or behavioral characteristic and
digitize it, or it can be the system that compares that captured
characteristic against other stored
biometrics.
At the very basic level, biometrics are used for two different
functions, biometric

verification and biometric identification. Through verification
or identification, multiple other
functions are capable. Biometric verification is the process of
verifying a claimed identity
through comparing a captured biometric from the individual
against a stored biometric associated
with that individual. Biometric identification is the process of
determining an individual’s
identity through a “one-to-many search” against the stored
biometrics of multiple people. This
search will either return zero matches, one match, or multiple
close matches which would be
candidates for the identity. Identification takes the best result
of the search and matches the
identity with the individual (Allan, 2013). Jefferson
summarizes biometrics well when she says,
“Biometrics is an enabling technology that makes possible:
tracking criminal histories and
solving crimes, protecting wide-ranging border areas, screening
individuals in high-volume
transportation conduits and protecting automated consumer

transactions” (2010, p. 101).
However, she only skimmed the surface of why biometrics can
be a technological solution for a
current problem.
A biometric modality is the type of biometric characteristic that
is being captured and can
also refer to the type of biometric system used to capture and
analyze that characteristic
(National Science and Technology Council, 2006a). The two
main categories of biometric
modalities are physical and behavioral modalities. Physical
modalities are those that measure the
physical traits of an individual such as fingerprints, iris, or
facial recognition. Behavior
modalities are those that measure an individual’s behavioral
characteristics such as keystroke
dynamics or gait analysis (IEEE, 2012). There is a relationship
between physical and behavioral
biometrics. Many behavioral biometrics are affected by the
physical characteristics of the
individual. For example, dynamic signature is a behavioral
biometric, but the signature stems
from the strength and dexterity of the individual’s hands and
fingers. Similarly, voice

recognition depends on the shape of a person’s vocal cords
(Allan, 2013).
There are many different biometric modalities that can be used
to identify individuals. If
there is a steady characteristic that can be measured, it is likely
that it can be used to identify or
authenticate an individual. Some of the most common physical
biometrics are fingerprint, face,
iris, vascular pattern, palm print and hand geometry recognition
(Modi, 2011). There are other
physical biometrics that are available including earlobe
biometrics. Some common behavioral
biometrics are keystroke dynamics, gait recognition, and
dynamic signature verification (Modi,
2011). Physical biometrics are usually unchanging, with the
exception of physical injury, and
“unalterable without significant duress”, but the capture of such
is often perceived as more
invasive than behavioral biometrics. However, behavioral
biometrics are generally less stable
than physical biometrics, usually changing over time and

susceptible to change from stress or
other factors (Allan, 2013, p. 12).
Fingerprint biometrics devices capture an image of the
fingerprint through a variety of
methods including optical, capacitive, ultrasound, and thermal
sensor to identify the minutiae,
friction ridges, and other identifiable parts of the fingerprint.
Then, the device or the system
converts the captured biometric image into a digital format
which can be transmitted and
automatically compared against other stored biometrics (The
FBI Biometric Center of
Excellence, n.d.). Fingerprint biometrics systems have an
accuracy rate of over 99% with two
fingerprints and 99.9% when using four fingerprints. The
number of fingerprints captured and
the quality of the fingerprint increase the accuracy of the
biometric system (Bulman, 2004).
Iris biometrics systems capture an image of an individual’s iris
which is the colored
portion of the eye. The system uses near infrared light to
illuminate the patterns of the iris
because it does not reflect like visible light and is also not
harmful to the individual. The

biometric technology is able to isolate the iris from the pupil,
eyelids and other pieces of the eye.
Similar to fingerprint biometrics, once the iris image is
captured, it is digitized and compared to
other stored iris biometrics (National Science and Technology
Council, 2006b). A person’s iris
patterns are created prior to birth through the folding and
forming of iris tissue and no two iris
patterns are the same. Additionally, a person’s iris patterns are
stable after age 3. Iris biometrics
have one of the lowest false acceptance rates with the odds of a
false acceptance rate for two iris
images is one in over one trillion (Clifton, 2013).
Vascular pattern recognition biometrics is a modality that uses
images of an individual’s
veins, usually in the palm. The technology uses an infrared
beam of light to illuminate an
individual’s hand or other body part and a camera on the other
side captures an image of the vein
patterns. This modality is very difficult to forge because the
veins are on the inside of the body.

Additionally, it is hygienic because it does not require the
individual to touch the machine in
order to capture the image of the veins. Vascular pattern
recognition is an accurate modality
with a false acceptance rate of less than 0.0001%, a false
rejection rate of 0.01%, and a very low
failure to enroll rate (Sarkar, Alisherov, Kim, & Bhattacharyya,
2010).
Keystroke analysis is a behavioral biometric modality that
evaluates how someone types
or uses electronic devices like smartphones or computers.
According to research by Charles
Tappert, our typing patterns are “consistent, predictable, and
nearly impossible to imitate”
(Stromberg, 2013, para. 3). Keystroke analysis can use measures
like the dwell time, how long
an individual presses an individual key, and the average time it
takes to transition between keys
to identify who someone is by how they are typing with an
accuracy of up to 99 percent
(Stromberg, 2013).
Multimodal biometrics systems use a combination of two or
more biometric modalities.

These systems use biometric identifiers with varying levels of
quality and accuracy and combine
them to make a very accurate system. Multimodal biometrics
systems improve accuracy because
there are more pieces of biometric information that are matched.
Additionally, multimodal
biometrics systems can be used if somebody is missing a body
part that is usually used for
biometric matching (Pellerin, 2004).
In the United States, there are three main national biometrics
databases managed by three
separate governmental departments. The three national
biometric databases consist of the
Federal Bureau of Investigation’s (FBI) Integrated Automated
Fingerprint Identification System
(IAFIS), the Department of Defense’s (DOD) Automated
Biometric Identification System
(ABIS), and the Department of Homeland Security’s (DHS)
Automated Biometric Identification
System (IDENT). FBI’s IAFIS database is managed by the
Criminal Justice Information Service

(CJIS) and is the largest criminal fingerprint database in the
world. Stored in the database are
biometrics for criminal offenses, known or suspected terrorists,
unsolved latent fingerprints, and
civil fingerprints of government employees and others (The
Federal Bureau of Investigation,
n.d.). DOD’s ABIS database stores biometrics from DOD
operations in foreign countries and
base access biometrics. Included in the ABIS database are
fingerprints from individuals
encountered in warzones, latent fingerprints from improvised
explosive devices (IED), foreign
employee access fingerprints, and foreign contractor
fingerprints (Biometric Identity
Management Agency, n.d.). DHS’s IDENT database is the
largest biometric database in the
United States and it stores biometrics from visitors to the
United States, criminal information
from individuals encountered by DHS law enforcement
agencies, and civil programs managed
by DHS agencies as well as biometrics shared with DHS from
other national and international
biometrics databases (Biometrics.gov, n.d.).
In addition to the three large national biometrics databases,

other local, state, and federal
agencies have biometrics databases that they keep for multiple
reasons. Some of the data in
these databases are fed into the larger national biometrics
databases. Outside of the United
States, several other countries have biometrics systems in place
for criminal offenses,
immigration, banking, and travel among other things. Many of
these countries have sharing
agreements in place with other countries, including the United
States, to share biometric
information of certain individuals, normally criminals,
terrorists, and citizens of other countries
(Homeland Security, n.d.).
Current Biometrics Uses in the United States and Abroad
Biometrics are currently being used for several different
purposes around the world. The
employment of biometrics is used to provide identity certitude
in a number of applications
including building access and financial applications. A 2008
survey conducted by Unisys found

that sixty-two percent of Americans were very concerned about
the safety of their personal
information and sixty percent were very concerned about credit
and debit card fraud (“Are we
learning,” 2008). In some applications, biometrics can be used
to protect personal information
and reduce the threat of credit and debit card fraud.
Biometrics are used throughout the world to track and screen
travelers as they seek to
enter different countries. Additionally, some countries have
taken steps to embed biometric
identifiers on chips in their passports and other travel
documents. All European Union member
states issue electronic passports and most of them have
extended access control (EAC) protected
fingerprints embedded. Additionally, many European countries
use automated border control
(ABC) measures. There are eight countries that currently have
ABC gates that primarily use
facial recognition. The ABC gates are located in Germany,
Spain, France, Finland, Netherlands,
Norway, Portugal and the United Kingdom. Additionally,
Austria, Belgium, Bulgaria, Czech

Republic, Denmark, Estonia, Hungary, Latvia, and Romania are
planning to implement the
biometrically enabled border gates (Wolf, 2013). The United
States takes biometrics from
travelers entering the country and, following the attacks of
September 11, 2001, required all
foreign visitors to hold valid passports and submit to biometrics
as a condition of entry.
(Alhussain & Drew, 2009). The United States has also deployed
kiosks at select locations that
allow for low-risk citizens and nationals of the United States
and six other countries if they are
enrolled in the Global Entry program. The participants will
present their passport to the kiosk
and will the kiosk will compare their fingerprint biometrics to
the ones on file and will then take
a photograph of the individual as a record of the encounter
(U.S. Customs and Border Protection,
2014). Australian Customs has also deployed automated
passenger processing systems at two of
its airports in Sydney and Melbourne. These “e-passport
SmartGates” allow for self-processing

by utilizing facial recognition biometrics to verify the identities
of the travelers and expedite
their process (Alhussain & Drew, 2009, p. 30). Biometrically
enabled turnstiles that use iris
matching technology can process 20-50 people per minute and
their accuracy is not impacted by
non-polarized glasses or sunglasses (Zalud, 2012). This
technology can expedite screening or
access at busy areas like train stations or airports.
In addition to identifying and tracking travelers, biometrics are
used by countries to
verify and identify their own citizens through a combination of
country issued identification
cards or other credentials and biometrics. Prior to incorporating
biometrics, the identification
cards were easily forged (Alhussain & Drew, 2009). The United
Kingdom issues asylum seekers
an identification card with two fingerprint biometrics
embedded. Japan uses biometric enabled
passports to reduce illegal immigration and terrorism (Alhussain
& Drew, 2009).
Biometrics are also used throughout the world for access
control and to restrict access to

only those authorized individuals whose biometrics match the
ones stored in the database.
Biometrics enabled access systems are often easy to manage
because individuals can be granted
access to certain locations and they may or may not need a
credential as well. Because the
system is managed electronically, it is easy to add, edit, or
remove access to sensitive areas.
Additionally, using biometrics can reduce the cost associated
with guards. At Yeager Airport in
Charleston, WV, biometric hand readers were incorporated with
a PIN or credential and video
surveillance system to control access to certain areas of the
airport. By installing this system,
individuals are able to quickly gain access to authorized areas
and the airport has saved
thousands of dollars. Prior to installing the system, the airport
was required to keep a guard 24-
hours a day at a cost of $25 per hour, but after installing the
$17,200 system, they no longer
needed the guard (Dubin, 2011). Scott Air Force base also
installed hand recognition systems

and saved over $4,000 in guard costs (Alhussain & Drew,
2009).
Biometrics are also used to keep track of personal interactions
to ensure that only
authorized individuals are receiving benefits or that no one is
abusing the system. For example,
biometrics are used for e-voting to ensure that no one is voting
more than once (Alhussain &
Drew, 2009). Biometrics are also used for candidate
verification purposes to identify or verify
an individual in order to receive benefits. Biometrics are used
in the healthcare field to verify the
individual’s identity in order to avoid health insurance fraud
and ensure the correct medical
records are being used (Allan, 2013). Additionally, biometrics
are used in some places to ensure
the correct student is taking a test instead of having an imposter
stand-in (Alhussain & Drew,
2009).
Additionally, in some countries that do not have strong identity
architecture, biometrics
are used to verify eligibility for benefits. For example, most
people in India do not have birth

certificates or other ways to identify themselves, but India has
established a nationwide biometric
database that is used to verify an individual’s identity and,
subsequently, their eligibility to
collect benefits and aid (Schneider, 2013). In some Latin
American countries, low income
families use biometrically enabled automated teller machines
(ATM) to withdraw a government
stipend used to send their children in school. The use of
biometrics ensures that only the
authorized individual is retrieving the money for their children
and also saves time and money
for the bank. The families do not access the ATM any other
time except to withdraw the stipend
and, prior to biometrics, would often forget their personal
identification number (PIN) or
password. The bank would then have to reset the information so
the family could access their
funds (Zalud, 2012).
In addition to using biometrics to access ATMs for government
aid, biometrics have been

used to withdraw money from ATMs and other financial
applications in several countries. Some
banks in Turkey, Brazil, and Poland use vein scan biometrics at
their ATMs. Additionally,
almost 80,000 ATMs in Japan use vein scanning biometrics
(Furlonger, 2013). Some banks in
Latin America use fingerprint scan biometrics at their ATMs
which reduce identify theft and
other problems associated with PIN enabled ATMs.
Additionally, using biometrics reduced the
number of people with multiple accounts under different
identities (Zalud, 2012). An additional
benefit to using biometrically enabled ATMs is that during
disasters or other exigent
circumstances, an individual may not have their identification
or bank cards, but they will always
have their biometrics. So, they would be able to access their
account and withdraw funds
without their identification because they are their own
identification (Furlonger, 2013).
Biometrics have also been used commercially in lieu of credit
cards or cash. The biometrics at
point of sale locations verify the person’s identity and authorize
the payment to the company

(Allan, 2013). Fatima lists several instances where banking
frauds have occurred in electronic
banking for amounts over $10 million and recommends that
using existing biometrics systems
could protect against those types of attacks (2011). By using a
two or three factor authentication,
with biometrics being one of the factors, banks and individuals
would protect their assets
because criminals would no longer be able to gain access by
stealing information such as user
names, passwords, or PINs (Fatima, 2011).
Biometrics systems are used by employers for a number of
reasons. As previously
discussed, they are used for access systems, but they are also
used for time and attendance
systems to ensure the correct individual is working and to
prevent another employee from
fraudulently clocking the individual in (Allan, 2013). In Saudi
Arabia, government employees
use fingerprint biometrics to ensure that the correct times are
recorded for when they start

working and when they end (Alhussain & Drew, 2009). Even
fast food restaurants are using
biometrics for employee accountability and security. At a
Kentucky Fried Chicken in West
Lafayette, Ohio, employees must use their fingerprints to access
the register which ensures that
only the appropriate employees have access to the registers and
ensures that employees will not
clock-in for each other (“Biometrics researchers,” 2013).
Biometrics can also be used in lieu of passwords. The use of
biometrics instead of
passwords can improve security and also save money and man
hours. Many passwords are
currently complex combinations of letters, numbers, and special
characters that are continuously
getting longer and more complex. Combined with the
complexity requirements of the passwords
and the requirement for most passwords to be changed
periodically, forgotten passwords can
reduce productivity and increase costs associated with
maintaining a help desk to reset
passwords (Jefferson, 2010). Additionally, due to the
complexity of passwords and the sheer
number of passwords to remember, many people write down

their passwords which counteracts
any security benefit of having a password. Biometrics can solve
the issue of passwords because
it is something that the individual always has with them and it
is also very difficult to steal
(Jefferson, 2010).
There are many other purposes that biometrics are used for.
According to Nelson in her
book American identified: Biometric technology and society,
“Biometric identification is also
part of a body of forensic systems used to identify missing
children, determine parentage, and
more generally investigate crimes” (2010, p. 2). Another
function that biometrics can enable is
scanning crowds to identify persons of interest on watchlists
containing terrorists, criminals, and
other people. This function is usually used in conjunction with
facial matching, gait analysis or
other stand-off biometrics (Allan, 2013). Casinos have been
using facial recognition software
for years to identify excluded gamblers or other unwanted

individuals. The system is more
accurate than having guards identify individuals or checking
identification and it is automatic
(Robson, 2011). Facial recognition biometrics were also used
during Super Bowl XXXV to scan
the faces of individuals as they entered the stadium in order to
identify terrorists or criminals
(Tavani, 2013). Other biometrics like face topography and
keystroke analysis are being used to
continuously authenticate an individual while using a system.
For example, biometrics can be
used while a person uses a computer system and can identify
when the individual walks away or
when someone else sits in front of the computer. This
technology eliminates the need for the
system to “timeout” and offers several forms of security
(LeHong & Fenn, 2013).
Previous Surveys
Several studies and surveys have been conducted concerning
biometrics and acceptance
of the new technology. Some of the studies evaluated different
biometric modalities while others
evaluated biometrics use for certain situations. This paper will
briefly discuss the previous

studies, their methodology, and the results.
In 1995, Deane, Barrell, Henderson, & Mahar conducted a
survey of 76 people for their
paper, Perceived acceptability of biometric security systems, to
determine the participants’
attitudes toward biometrics as well as their perceptions of
different biometric modalities. Deane
et al. discovered that biometrics were rated less acceptable than
passwords (Riley, Buckner,
Johnson, & Benyon, 2009). In 2001 and 2002, Opinion
Research Corporation (ORC)
International (as cited in El-Abed, Giot, Hemery, &
Rosenberger, 2010), conducted two different
phone surveys of 1017 and 1046 adults living in the United
States to determine their acceptance
of biometrics systems. More than 75% of the participants felt
that biometrics were acceptable
for United States law enforcement authorities to verify identity
for passports, for airport check-
ins and to obtain a driver license. Also, 77% of the participants
felt that fingerprint biometrics

could protect individuals against fraud. However, greater than
85% of the participants worried
about their personal information being misused (El-Abed et al.,
2010).
In 2004, another survey was conducted to determine the attitude
toward biometrics in the
context of air travel. The BioSec 2004, survey had 204
participants from Finland, Germany, and
Spain. Most of the survey participants had positive attitudes
towards biometrics for air travel but
over half were afraid of losing their privacy. Additionally, 25%
were concerned about health
risks from using the biometric technology and 20% worried
about the hygiene of the systems
(Riley et al., 2009). In 2005, the UK Passport Service
conducted a biometrics enrollment trial
(as cited by Riley et al., 2009) with over 10,000 participants
from multiple locations in the
United Kingdom. This study determined that most participants
had a positive attitude toward
using biometrics in conjunction with national passports, but
almost 25% of the participants were
concerned about the effect of the technology on their civil
liberties (Riley et al., 2009).

In 2007, Nelson conducted a national telephone survey of 1,000
individuals in the United
States of America to gather public opinion of privacy and
biometric technology. The
participants ranged in age from 18 to 93 years old with 57.6%
female and 42.3 male
participation. The average age of the participant was 51 years
old. Ninety-two percent of the
participants were high school graduates and 39% held at least a
4-year college degree. The
topics of the telephone survey included the importance of
protecting personal information,
threats to information privacy, comfort level with privacy
protection measures, and attitudes
toward biometric technology (Nelson, 2010).
In addition to the telephone survey, Nelson conducted a study
using focus groups to
“understand the views of biometric users and nonusers on a
variety of issues related to how
private information is protected and used by different
institutions and to understand how

biometric technology can potentially safeguard that private
information and provide security”
(Nelson, 2010, p. 19). Nine focus groups from 55 participants
were created with biometric users
being grouped with other users and non-users grouped with non-
users. The focus group study
was conducted as a mixture of a survey and a moderated in-
depth discussion following the
survey to further explore participants’ attitudes and opinions
(Nelson, 2010).
As cited by El-Abed et al., the results of a NIST survey on
biometrics usability of
fingerprints was published in 2007 (2010). The NIST survey
was conducted by 300 adults
consisting of 151 women and 149 men ranging in age from 18
years old to over 65 years old.
This survey was conducted to identify users’ acceptance of
fingerprint biometric systems. The
majority of the participants were in favor of using fingerprint
biometrics to verify identity for
passport purposes with 77% saying they agreed with the use in
that situation. Additionally, 2%
of the participants were concerned about the cleanliness of the
devices that they would have to

touch to use (El-Abed et al., 2010).
A 2008 survey conducted by Unisys (as cited by “Are we
learning,” 2008), determined
that the majority of United States citizens were comfortable
with biometrics for authentication.
Over 70% of the participants would trust government agencies
and banks to use their biometric
data to verify their identity and fingerprints tied passwords as
the primary preferred method of
authentication. The Unisys Security Index survey also
determined that 62% of Americans were
very concerned about the safety of their personal information
and 60% were very concerned
about credit card fraud. Additionally, the survey determined
that American citizens were less
supportive of blood vessel scans with only a 43% acceptance
rate as compared to the 73%
acceptance rate of fingerprint biometrics. Men and women were
also determined to have similar
acceptance rates for using biometrics to verify their identity,
but women were less willing to use

advanced biometric methods like eye scans and hand scans
(“Are we learning,” 2008).
In 2009, Riley et al. conducted a survey of quantitative and
qualitative questions to
determine people’s attitudes towards biometrics in three
different countries, India, South Africa,
and the United Kingdom. The survey was written in English
and administered electronically.
The study had 581 participants with 202 from India, 202 from
South Africa, and 177 from
United Kingdom and almost an even divide between male and
female participants. The
questions on the survey asked about “perceived privacy, safety,
usability and acceptability of
biometrics” (Riley et al., 2009, p. 299). Additionally, an open-
ended question was included in
the survey to allow the participants to expand on their opinion
of biometrics. About half of the
participants answered that question. The survey had limitations
associated with how it was
administered. It was administered in English and, while many
people in the countries speak
English, it is not their first language. Additionally, the
participants from India and South Africa

were compensated for their participation and that could impact
the responses. Riley et al. also
note that the requirement to be proficient in English introduced
sampling bias into the survey
which means that the results of the survey would apply to a
subset of the population and not
necessarily the general public (2009).
In 2009, Alhussain & Drew described their study in their paper
Towards user acceptance
of biometric technology in E-government: A survey study in the
Kingdom of Saudi Arabia.
Alhussain & Drew conducted interviews of 11 managers in
different management levels and
conducted a questionnaire of 101 employees in the Saudi
Arabian government to determine
perceptions of biometric authentication in the workplace. The
managers were asked five open-
ended questions to get a qualitative result. The questions asked
about if there was a perceived
cultural gap for their employees and if the managers felt a level
of responsibility for narrowing

that gap. Additionally, they asked about any difficulties and
barriers to implementing
biometrics. The survey that was given to the 101 employees
was answered quantitatively on a
five point scale. The employees were asked how important they
thought biometrics were to the
organization, if they thought that biometrics meant that their
employer mistrusted employees,
and if they thought there should be an awareness of biometrics
before implementation (Alhussain
& Drew, 2009).
In their paper A study of users’ acceptance and satisfaction of
biometric systems, El-Abed
et al. discuss their study they conducted to study perception of
biometrics to improve the
usability of biometric systems (2010). The study used 70
participants consisting of 71.4%
students and 28.6 employees from different countries to answer
survey questions after using two
different biometric systems. The participants used a keystroke
verification system and a face
verification system. Then, they answered 23 survey questions
about their demographic

information, general perception of biometrics and their
perception of the tested biometric system.
Their study found that 33.3% of the participants did not trust
the face verification system and
23.2% did not trust the keystroke verification system.
Additionally, the participants were much
more concerned about their privacy when using the face
verification system as opposed to the
keystroke system. Additionally, the participants felt that the
keystroke verification system
performed better than the face verification system with 89.9%
of participants satisfied with the
keystroke biometric and 81.1% satisfied with the facial
biometric. Even though the keystroke
biometric outperformed the facial biometric, participants
preferred the facial biometric for
certain applications. For logical access, 56.5% of the
participants prefer keystroke verification
systems while 26.1% prefer face verification systems. For
physical access, 36.2% prefer to use
face verification systems and 14.5% prefer to use keystroke
verification systems. If they had to

choose one system for both applications, 31.9% of the
participants would prefer to use face
verification systems while 26% would prefer to use keystroke
verification systems (El-Abed et
al., 2010).
In 2013, Miltgen, Popovic, & Oliveira wrote about the study
they conducted to determine
what the key determinates of end-user acceptance of disruptive
information technology like
biometric systems are. The survey was scenario based and was
administered electronically to
326 European participants between the ages of 15-25 years old.
The majority of the participants
were students in a range of education levels. The scenario was
written as a friend has an
opportunity to use iris scan biometrics to identify himself or
herself before a driving test. The
iris scan will allow the friend to bypass a line and will
automatically assign a machine for him or
her to use. Based on the scenario, participants were asked to
answer questions on the perceived
usefulness, compatibility, perceived risks and other aspects of
the biometric technology (Miltgen,

Popovic, & Oliveira, 2013). The survey has several limitations
including that it only focused on
one biometric modality, only had participants between 18-25
years old, and only had European
participants.
Concerns About Biometrics
Concerns and objections to using biometrics can be based on
many different things.
Someone may object to using biometrics based on the situation
in which the technology is being
used. In this example, the person objects to the purpose for the
biometrics, but not the
technology itself. Other concerns about biometrics stem from
opinions or beliefs of the
individual revolving around loss of privacy, health risks,
hygiene, and lack of trust in the
technology. In other cases, the individual may not object to the
technology or the purpose of the
use, but they may not trust the government or organization that
is using the biometrics. The
individuals may be afraid that their information is not being

used appropriately.
The distrust of the government or the organization using the
biometrics combined with
current events has the potential to sway the views of
individuals. For example, during the survey
conducted by Riley et al., there was a proposal for a national
identity card in the United
Kingdom that would be a mandatory requirement and would
require the collection of biometric
data. This proposed identity card received a lot of negative
media attention around the time of
the survey and the researchers believed that negative attention
could have accounted for the
lower than expected level of acceptance in the United Kingdom
(Riley et al., 2009). The recent
media attention on the National Security Agency (NSA) and
their domestic spying program has
caused more attention and negative feelings to be directed to a
DHS facial recognition program
in development called the Biometric Optical Surveillance
System (BOSS) (Gonsalves, 2013).
This recent attention to misuse of private information by the
government and the violation of

trust by U.S. citizens has the potential to impact the results
from the survey conducted in this
study.
Lack of trust in the government is not a new phenomenon. The
National Biometric
Security Project reported that the three government agencies
that use biometrics to protect
against terrorism are also the three government agencies that are
the least trusted by American
citizens. The Department of Justice, the Department of
Homeland Security, and the Central
Intelligence Agency were the three government agencies that
participants of a poll ranked as
least trusted to protect their personal information (2006). The
National Biometric Security
Project also highlights another reason that American citizens
may not trust biometrics and central
databases containing their information. Their report states,
The very existence of a central database concerns people who
recall times when the
government used databases of information on people for
purposes far beyond their

original intent. Examples of reported misuses include the use of
confidential information
from the Census Bureau during World War II to locate and
intern Japanese-Americans
and the use of confidential information from the National Crime
Information Center to
monitor people opposed to the Vietnam War. Both of these
reported misuses of
information contained in confidential databanks took place
when the country was at war.
Accordingly, during today’s time of instability when fears of
future terrorist attacks
abound, it is not unreasonable to anticipate that some people
will be concerned that in the
future, biometric data gathered to screen for terrorist could be
used for other purposes or
associated with other data about the individual.
(National Biometric Security Project, 2006, p. 81)
In addition to citizens having low acceptance to centralized
biometric databases due to mistrust

in the government, individuals do not trust the centralized
databases due to the potential for their
personal information to be compromised (Riley et al., 2009).
Respondents worry that if
biometric template data in the database is compromised, the
information will be compromised
forever without a solution (El-Abed et al., 2010).
A major concern that many participants in previous studies had
with biometrics is the
potential loss of privacy associated with biometrics use.
Miltgen et al. state that privacy
concerns are source of public aversion to biometrics. They go
on to say that the privacy
concerns can be linked to the personal nature of biometrics
because there is a link between an
identity and the individual’s body (2013). The privacy concern
varies by the location in which
biometrics are used and the purpose for their use. Views on
privacy differ drastically between
the United States and European countries. Rosen illustrates the
difference between American
views on privacy and European views when he states,
“Americans tend to be much more
concerned about government surveillance while Europeans tend

to be more concerned about
privacy invasions by the private sector” (2007, p. 295). Rosen
goes on to suggest that, although
Americans have privacy concerns, they may give up their rights
to privacy for individual
purposes when he states, “A society where citizens refuse to
respect their own privacy is not one
where privacy will be long respected; and the American
experience suggests that citizens in an
individualistic market democracy may perceive too many market
rewards for exposure to respect
their own privacy for long” (Rosen, 2007, p. 299).
Other concerns with biometrics that are commonly stated by
participants in studies
involve the misuse of their personal data, health risks associated
with the use of biometrics, and
hygiene issues associated with use of the technology. Riley et
al. reported that individuals were
concerned that their biometric information could be used for
marketing or other commercial
purposes (2009). Another concern noted by Riley et al. is that

function creep could cause
biometric information to be used in situations and functions
other than it was originally agreed to
be used for (2009). Many people have concerns that use of
biometrics devices can pose health
hazards. These concerns are especially relevant with advanced
biometrics like iris or retina
scanners. When biometric devices were used in Saudi Arabian
government buildings, some
employees were concerned that the devices could cause skin
cancer (“Careful with,” n.d.). El-
Abed et al. also noted that previous studies found that some
users complained that hand
geometry biometric devices could dry out their hands and some
military aviators were concerned
that retinal scanners could damage their vision (2010). The
2004 BioSec survey (as cited by
Riley et al., 2009) noted that 20% of the participants had
concerns about the hygiene of
biometrics systems that required contact. The ability for some
biometric technologies, like
retinal scans, to disclose disease or health issues is another
reason that some users to do not
approve of the technology (Nelson, 2010).

Cultural issues and attitudes play a major role in concerns and
acceptance of biometrics.
During a discussion with a developer of biometrics technology,
the developer stated that cultural
attitudes were a driving factor in changing the color of the
illuminated fingerprint platen on their
biometrics device. The original fingerprint reader was
illuminated in red, but many users
reported that, due to language differences and lack of
interaction with technology, some
individuals were afraid of the red platen due to misconceptions
that it would be hot or other
reasons. The developer changed the color from red to green and
there were fewer concerns.
Other cultures may have an aversion to touch with public
sensors and having to place a body part
on a biometric device may be unacceptable (El-Abed et al.,
2010). There are many factors that
determine a culture’s acceptance of biometrics. Experience and
acceptance of other technology
in a culture generally increases biometrics acceptance. South

Africa has a high rate of violent
crime and, subsequently, many individuals from that country
have a fear that their biometric
identifiers will be removed for criminal purposes and they will
be harmed (Riley et al., 2009).
Lack of trust in the biometrics system and the accuracy of the
technology is another
major impediment to acceptance. Many participants in the
study conducted by Riley et al.
expressed concern about the reliability of the biometrics
equipment and the potential
consequences to the individual if the technology failed (2009).
Additionally, some individuals
have problems using some biometric modalities due to their
physiological characteristics.
Gartner finds that a few individuals out of a thousand
experience problems using fingerprint
biometrics for authentication (LeHong & Fenn, 2013). This fact
does not build trust in the
system reliability. Biometric systems can also be spoofed using
several different methods. Modi
describes several methods to spoof biometrics systems including
using false fingers out of
silicon, transferring a latent print to a piece of tape and using

that in place of a finger, using high
resolution photos to trick face recognition software, using
contact lenses to fool iris recognition
devices, using plaster molds of a hand to spoof hand geometry
systems, and using vein patterns
printed on paper to fool vascular pattern recognition devices
(2011).
Mitigating Measures to Address Concerns
Much of the literature written has identified some solutions to
mitigate the concerns
individuals have about biometrics. To prevent spoofing, many
biometrics systems have
countermeasures built in. For example, many biometrics that
contact the individual use heat
sensors and other liveness detection methods to ensure there is
an actual live person touching the
machine. Other biometric modalities use features like eye
detection and examination of the skin
properties to detect masks of other methods of deception in
facial recognition (Modi, 2011).
Liveness detection measures also address concerns by some

individuals that their biometric
identifier could be forcefully removed and used. The liveness
detection would detect that the
biometric was no longer “alive” and would reject it.
Many of the concerns that biometrics can cause health
problems can be discounted. Iris
and retinal scans do not cause damage to the eyes because they
use low output light emitting
diodes (LED) to illuminate the eye with near infrared light in
order to take a photograph of the
biometric features of the iris or the retina. The output of the
LED is low to minimize any risk for
damage to the eye (National Science and Technology Council,
2006b). Biometrics systems are
designed and tested to minimize any health risks to individuals.
Additionally, health concerns
from the hygiene of the biometrics device can be addressed by
using contactless biometric
systems like iris recognition or vascular pattern recognition.
Contactless systems can also
minimize objections due to cultural aversion to touching public
sensors (El-Abed et al., 2010).
Although there may be privacy concerns with biometrics use,
the technology can provide

more security of personal information than other security
alternatives. Allan states, “Because
biometric traits are more difficult to copy or share than
passwords and tokens, biometric
authentication can provide a higher level of accountability than
any alternatives, and may be
used alone or in conjunction with other technologies when
individual accountability is
paramount” (2013, p. 8). Additionally, to address concerns
about compromised biometric
templates, there are several methods for protecting templates
and identifying compromised
templates. Biruntha et al. state that steganography,
watermarking, and cryptography can be used
to protect templates and detect compromises (2012). Biometrics
templates can also protect
against fraud because if they are compromised, they can be
revoked and replaced with a new
template (Jefferson, 2010).
To address concerns of biometrics systems not working
correctly or not accepting an

individual’s biometrics, multi-modal biometric systems can be
used. Utilizing multiple
modalities when enrolling individuals in the databases
maximized the searchable biometric data
and reduces the number of individuals that cannot be enrolled or
searched due to missing or poor
quality biometric characteristics. Additionally, using multi-
modal capable biometrics systems to
search or verify individuals allows for the system to take the
best quality biometrics to verify
against the database (Dessimoz, Richiardi, Champod, &
Drygajlo, 2007). Also, the accuracy of
the system increases with each added modality. Using multi-
modal systems with reduce the
number of false matches and in turn would improve trust in the
accuracy.
Actions to Improve Acceptance
In order to improve acceptance of the technology, the concerns
of the population need to
be addressed. As previously mentioned, many of the concerns
individuals had revolved around
the loss of their personal information, their information being
used for purposes other than what

they agreed to, potential health concerns, and the potential that
the biometric device is not
accurate or inoperable. Many of the concerns stemmed from
lack of knowledge of biometrics
technology and the mistrust of the agencies conducting
biometrics. The mitigating factors to
their concerns mentioned earlier can be used to relegate their
concerns.
One action that can be taken to improve acceptance of
biometrics is to improve
knowledge of biometrics and their use. The research has shown
that, generally, the people that
know the most about the technology feel more comfortable with
it and are more supportive of it.
In the BioSec 2004 survey (as cited by Riley et al., 2004), the
German respondents were the most
knowledgeable about biometrics and, subsequently, had the
most positive attitudes toward the
technology. Another thing that technology developers can do to
improve acceptance of their
product is to identify sources of resistance early in the research
and development process.

Mitchener-Nissen recommends that developers engage the
public early in the design process to
identify concerns and translate those concerns into design
requirements to minimize social
resistance “before it coalesces and becomes synonymous with
the technology being developed”
(2013, p. 3). LeHong & Fenn claim that increased user
experience and increased assurance of
the accuracy of the technology combined with lower cost and
improved convenience features of
biometrics will improve acceptance of biometrics technology
(2013).
To address the concerns that the biometrics and personal
information will be used for
purposes other than their original purpose including tracking
individuals can be addressed by
conducting privacy assessments and making those documents
publically available (Jefferson,
2010). The privacy impact assessment for the U.S. Department
of Homeland Security’s
biometric database, IDENT, is publically available on the DHS
website and details the purpose
for the biometrics system, who can use the system, who
biometrics can be collected from, why

biometrics may be collected, any privacy risks associated with
the system and steps taken to
mitigate those risks, as well as other information that the public
would want to know (U.S.
Department of Homeland Security, 2012). Similarly, the FBI
makes the privacy impact
assessments for their biometrics systems publically available on
their website for many of the
same reasons as DHS. The FBI IAFIS privacy impact
assessment describes the background for
why the biometrics system is needed, how it will be used and
what protections individuals have
in addition to other information an individual may want to
know. The privacy impact assessment
also describes partnerships with other agencies and databases
(The Federal Bureau of
Investigation, 2012). Individuals can read the privacy impact
assessment and see that their
information is being used for specific purposes and that it is
being protected within the bounds of
the privacy impact assessment.

However, if individuals do not trust the government, agency or
corporation that is using
biometrics, any document published by that organization will
not appease many of the concerns
of the individuals. Then, the only way to improve acceptance of
the technology is to show the
public that the organization can be trusted and gain the trust of
the individuals. The other way to
gain acceptance of biometrics is to use the technology for
reasons that improve convenience for
the public. For example, by using biometrics in the place of
passwords, individuals would not
have to remember multiple, complex passwords that have to be
changed periodically (Jefferson,
2010). Additionally, programs like CBP’s Global Entry
program can build acceptance for
biometrics because it uses the technology to provide a
convenience feature that allows
individuals to more quickly check into customs and avoid long
lines (U.S. Customs and Border
Protection, 2014).
Remaining Questions
The research and associated literature have identified many

factors in individuals’
attitudes towards biometrics technology and their acceptance of
their use. However, some of the
research is dated and needs to be revisited periodically to
determine if the findings are still
relevant. One question that needs to be answered is, “How have
the attitudes of the individuals
changed in the past few years?” With every year, technology
becomes more and more embedded
in the everyday life of individuals. With the influx of
technology, people become more
comfortable with technology and in-turn more comfortable with
biometrics. However, recent
current events and media coverage have the potential to change
the opinion of the American
public. Recent media coverage of the National Security
Administration’s actions has caused
many citizens to be concerned about their privacy. Similar to
the UK’s biometrics results in the
study conducted by Riley et al., if surveyed now, citizens of the
United States may not trust that

their information would be protected and used appropriately
which would negatively impact
acceptance of biometrics.
Methodology
Data Collection Technique
The study was conducted in two parts. The first part of the
study was an intensive
literature review of the existing biometrics literature to learn
what other researchers have
identified as impacts to biometrics acceptance. Additionally,
the literature review identified
previous surveys that researchers had conducted and those
surveys and their results were used to
develop the second part of the study.
The second part of the study was an anonymous online survey
that was designed to
collect and analyze participants’ opinions of biometrics and
their thoughts on acceptable uses of

the technology. The survey was created and administered using
Google’s forms functionality on
Google Docs. The survey consisted of five demographic
questions, 19 multiple choice
quantitative questions, and four fill-in-the-blank qualitative
questions. The results of the survey
were compiled in Google Docs using their spreadsheet
functionality. A copy of the survey
questions is included in this report as Appendix A.
The five demographic questions were multiple choice and
designed to gather information
such as the age of the participant, level of education, gender,
and experience with biometrics.
This data was used in the analysis to identify differences in
opinions based on demographic
characteristics. Additionally, the demographic information was
used to compare the sample
makeup to the overall population of the United States in order
to validate the results of the
survey. The 19 quantitative questions were divided into five
separate groups of questions
designed to gather data for different aspects of the study. Each
question had five answers for the
participant to choose from. The first section consisted of four

multiple choice questions
designed to measure the participants level of comfort with using
biometrics technology in the
different situations in each question. The participants chose
between the five answer options of
very comfortable, somewhat comfortable, unsure, somewhat
uncomfortable, or very
uncomfortable. The second section consisted of five questions
with the same options for the
participants to choose from as the first section. This section
was designed to measure the
participants’ level of comfort with different biometric
modalities. The third section consisted of
four questions designed to measure the participants’ acceptance
with different uses of biometrics.
The participants chose between the five answer options of very
acceptable, somewhat acceptable,
unsure, somewhat unacceptable, or very unacceptable. The
fourth section consisted of four
questions with the same answer categories as the third section.
This section was designed to

measure the participants’ level of acceptance with different
implementations of biometrics
technologies. The fifth section consisted of two questions
designed to capture the participants
overall opinion of biometrics and their roles in security and
convenience. To answer these
questions, the participants chose between the answer options of
very significantly, somewhat
significantly, unsure, very little, or none.
The four qualitative questions were designed to gather any
suggestions that the
participants had without being constrained by the limit or
format of the multiple choice options
of the quantitative design. Additionally, they were designed to
capture the general attitude and
opinion of the participants in their own words. The first
narrative question aimed to identify
locations where biometrics would be beneficial. The second
question was designed to identify
instances and situations where biometrics were needed for a
specific purpose. The third question
aimed to identify specific criteria that needed to be met in order
to use biometrics technology in
an acceptable manner. The fourth question was designed to

gather criteria for the unacceptable
use of biometrics and identify when biometrics collection would
be objectionable to the survey
participants.
Subjects and Setting
The survey participants were solicited from a small population
of people known by the
author and the faculty advisor. Participation was solicited
through the use of notifications on the
social networking site, Facebook, and emails sent to faculty and
students of American Military
University as well as co-workers, friends, and family of the
author. The notifications and emails
explained the purpose of the survey, requested their
participation, and provided the link to the
online survey. There were no identification numbers assigned
to the survey links and no way of
identifying who participated in the survey as it was completely
anonymous with the exception of
the demographic information which had little to no identifying
information.

The solicitation on Facebook was conducted as a status
message with a request for the
author’s “Facebook friends” to complete the survey with a link
to the survey location. Of the
almost 300 acquaintances on Facebook, it is expected there was
a five to ten percent participation
rate in the survey. The 300 individuals ranged from over 18
years old to over 80 years old, in a
variety of occupations, with varying levels of education, and
geographically located all over the
United States. The author’s co-workers are all employed by the
United States Coast Guard,
located in Washington, D.C., between the ages of 25 years old
and 60 years old, and most have
at least a Bachelor’s degree. There were less than 30 co-
workers that were asked to participate in
the survey. The students and faculty of American Military
University were all well-educated
with all of them having at least a Bachelor’s degree.
Additionally, they were all over 24 years
old, employed in many different occupations, and
geographically located all over the United
States.

Statistical Analysis
For the quantitative portion of the study, each question had five
choices of answers. Each
of those answers was converted to a value between one and five.
Additionally, each of the
questions was assigned a question number for easier charting
and analysis. Then, the results of
the survey were placed into an Excel spreadsheet where they
were studied and analyzed. First,
the average of each question was calculated. Then, the standard
deviation and variance were
calculated. Once those values were calculated for the entire
population, the spreadsheet was
used to filter the results by demographic characteristics and the
same calculations were
conducted for the different characteristics. Those results were
compiled and placed in tables
where they were subsequently graphed. The researcher
compared the results in each category
against the overall average and against the other categories to
develop assumptions about the

demographic subsets. Additionally, the researcher considered
the number of participants from
each category when considering the significance of each
subset’s average. If the category had a
small number of participants, its results were not given the same
regard as a category with many
participants because the average of the smaller category could
be more greatly impacted by the
answers of one or two participants. This would not lead to a
fair and accurate categorization for
those demographic subsets.
Limitations of the Study
The study was limited by the amount of time available to
complete it and the number of
participants that completed the online survey. As the study was
conducted in order to complete a
thesis to fulfill a requirement for a Master’s degree program,
the author was constrained by the
amount of time available in the course and in order to complete
the study in time, the author used
a small population of participants that would respond quickly.

For this study, the survey was
open for two weeks and had 69 participants complete the
questionnaire.
Another limitation in the survey was the potential lack of
diversity in the participants and
the disparity with the larger population of the United States of
America. The participants of the
study were predominately male with only 33% of the
participants being female. According to a
2012 census study, almost 51% of the population of the United
States was female (United States
Census Bureau, n.d.c). Additionally, an overwhelming number
of the participants in the study
had obtained a higher level of education than the national
average. Forty-one percent of the
participants had obtained a Master’s degree and 20% of the
participants had obtained a Doctorate
degree while the national average in the United States was that
8.41% of the population had
obtained a Master’s degree and 1.68% had obtained a doctorate.
Additionally, 35% of the survey
participants had obtained a Bachelor’s degree which was higher
than the national average of
20.09% (United States Census Bureau, n.d.b.). Another

disparity between the survey sample and
the population of the United States was the number of military
members that participated.
Almost 28% of the participants in the survey were military
which was much higher than the
national average of less than 1% of the population (National
Public Radio, 2011). Also, the age
dispersion of the survey participants was not as varied as the
population of the United States.
There were over three times the percentage of 25-34 year olds
represented in the survey than in
the population of the United States. People between the ages of
25 and 34 comprise 13.4% of
the population of the United States. However, they made up
43% of the participants for the
survey. Similarly, 28% of the survey participants were between
the ages of 35 and 44 years old,
but only 12.9% of the population of the United States are in that
age range. The percentage of
survey participants between the ages of 45 and 64 years old was
very close to the percentage of

the United States population with 23% of survey participants
and 26.5% of the U.S. population
falling in that range. Survey participants 65 years old and older
were underrepresented in the
survey with only 6% of the participants falling in that age range
when the national average is
13.4% of the population is 65 or older (United States Census
Bureau, n.d.a). These limitations
can be attributed to the sample populations chosen for the
survey and the method used to gather
data. Because the survey participants were solicited using
online social media to reach out to
acquaintances of the author and emails were used to reach out to
co-workers of the author and
students and employees of the American Military University,
there was not much diversity
present in the participants.
Results
Demographics and Response Distribution

The study had 69 participants complete the survey. Of those
participants, 67% were
male, 43% were between the ages of 25 and 34 years old, 41%
held a Master’s degree, 20% held
a Doctorate degree, 58% were employed for wages (other than
military), 28% were active duty
military, and 55% had some experience with biometrics but
would not consider themselves to be
very experienced. The number of participants from each
demographic group are reported in
Table 1. Additionally, the distributions of each demographic
group are illustrated in Figures 1-5.
Figure 6 shows the number of times each answer was chosen
for each quantitative
question on the survey. As previously stated, the terms used for
the answers on the quantitative
questions were converted to values between one and five for
analysis. Depending on the section,
an answer with the value of one would correlate to the terms,
Very Uncomfortable, Very
Unacceptable, or None. Likewise, an answer with the value of
five would correlate to the terms,
Very Comfortable, Very Acceptable, and Very Significantly.
Additionally, for the purpose of

analyzing and graphing the results, each quantitative question
was assigned a question number.
Table 2 lists the quantitative questions and their assigned
question numbers.
The answers for each qualitative question were reviewed and
placed into categories with
similar answers. Those categories were then tallied and
graphed. The number of results could
be further minimized by placing them in fewer, broader
categories. The results of the qualitative
study can be seen in figures 7-10. There are more qualitative
answers than there were
participants because some participants listed multiple answers
for each question. For the
question that asked the participants to list locations where
biometrics would be most beneficial,
14% listed locations that have restricted access control, the next
two highest answers were
airports and banks with 11% and 9% respectively. The results
from this question can be seen in
figure 7. The question that asked participants to list instances
where biometrics are needed had a

closer distribution of answers. The answer chosen most often
was for restricted access control
with 10%. Boarding a flight, identity
verification/authentication, and medical were the next
three popular answers with 9%, 9%, and 8% of the answers.
The next eight answers ranged from
4% to 6%. The results from this question can be seen in figure
8. When participants were asked
to list acceptable uses of biometrics, almost twice as many
responses were for restricted access
control than any other answer. The next three highest responses
for this question were national
security, same as above, and hospital access or medical
identification with 8%, 8% and 7%. Due
to the aggregate nature of the responses, the researcher was not
able to correlate the “same as
above” answers to any of the answers for the previous
questions. The results for this question
are located in figure 9. When asked to list unacceptable uses of
biometrics, the participants were
overwhelmingly against using biometrics for marketing,
commercial purposes, or selling data to
third parties with over 40% of the responses. The next two
most common responses for

unacceptable use were “routine use or common daily activities”
and “large spectator events or
sporting events” with 8% and 7% respectively. The results from
this question are in figure 10.
Table 1
Number of Participants by Demographic
Gender Age Education Employment Experience
Male 46
25-34 30
Some college, no
degree 2
Employed for
wages 40
No Experience 23
Female 23 35-44 19 Associate Degree 1 Self-employed 1
Some Experience 38
45-54 7 Bachelor's Degree 24 Homemaker 1 Very
Experienced 8

55-64 9 Master's Degree 28 Student 1
65+ 4 Doctorate Degree 14 Military 19
Retired 7
Figure 1: Gender Distribution of the Sample Population
Figure 2: Age Distribution of the Sample Population
Figure 3: Education Distribution of the Sample
Population
Figure 4: Employment Distribution of the Sample
Population
Figure 6: Response Distribution by Question

Figure 5: Experience Distribution of the Sample
Population
Table 2
Quantitative Questions
Question
Number
Question
1
Please indicate your level of comfort with the following
situations [How comfortable are you with
providing biometrics to log into your personal computer or
phone?]
2
providing biometrics to board a flight?]
3

providing biometrics to "clock-in" for work?]
4
providing your biometrics to withdraw cash from an ATM?]
5
biometric types [Given that you agree with the
purpose or reason for biometrics use, how comfortable are you
with providing a scan of your iris? ]
6
with providing a scan of your fingerprints?]
7
with providing a scan of your palm prints?]
8
with providing a scan of your face?]

9
with allowing a scan of your veins for vein
pattern recognition?]
10
For the following scenarios, choose your level of acceptance
(Part I) [Your biometrics are captured and
transmitted in an unencrypted format.]
11
(Part I) [Your biometrics are captured and
transmitted in an encrypted format.]
12
(Part I) [Your biometrics are stored in a
secured government database and can only be accessed for
approved reasons such as homeland security or
law enforcement.]
13
(Part I) [Your biometrics are stored in a

database and can be accessed by commercial companies for
targeted advertising.]
14
(Part II) [Using biometrics to screen
individuals at a public event.]
15
(Part II) [Using biometrics to replace
passwords.]
16
(Part II) [You were informed of the
implementation of biometrics three months prior to it becoming
required.]
17
(Part II) [You were not informed that
biometrics would be required.]
18 Based on your understanding of biometrics.... [How much
does the use of biometrics improve security?]
19
Based on your understanding of biometrics.... [How much does
the use of biometrics improve

convenience?]
Figure 7: Qualitative Question #1 Responses Figure 8:
Qualitative Question #2 Responses
Fi
gure 9: Qualitative Question #3 Responses
Figure 10: Qualitative Question #4 Responses
Impact of Education
Those participants with advanced Masters or Doctorate degrees
answered lower than the
average answer on almost all of the questions of the study.
Those participants that Bachelor
degrees averaged the same or higher than the average response
on almost all of the questions.

Due to the low number of participants with an Associate Degree
or some college, but no degree,
the results of their questions were not used to formulate the
opinion of how education impacts
biometrics acceptance. Participants with Bachelor Degrees had
an average answer of 1.1 while
participants with Doctorate Degrees and Masters Degrees had an
average answer of 1.4 and 1.5
respectively which was higher than the overall average response
of 1.3 for question number 13
relating to commercial use of biometrics. Although close with
averages within 0.2, the responses
from the participants with Masters Degrees were higher on
average than those with Doctorate
Degrees with the exceptions of questions number 4, 7, and 11.
Participants with Bachelor
Degrees averaged at least 0.4 higher than the average
participant on questions number 3, 6, 7,
and 12. Figure 11 shows the difference in the average answer
by participants in each education
level.

Figure
11: Impact of Education on Biometrics Acceptance
Impact of Different Modalities
This survey had 5 questions that asked participants to choose
their level of comfort with
the following biometric modalities, iris scan, fingerprint scan,
palm print scan, face scan, and
vein pattern recognition. Those modalities correlate to
questions 5-9 on the survey respectively.
As seen in Figure 11, the average response for iris scans and
facial scan, question 5 and 8, was
3.6 while the average scores for fingerprint scans and palm print
scans, question 6 and 7, were
4.2 and 4.1. Vein pattern recognition, question 9, had the
lowest average score with 3.3.
Impact of Gender and Age
There were slight differences between the results from the male
participants and the
female participants in this study. The questions with the largest
difference were question 17 with

a difference of 0.6, question 8 with a difference of 0.5, and
questions 2, 3, and 9 with a
difference of 0.3. Males had higher responses than the average
for questions 1, 2, 3, 8, 9, 13, and
17. Females averaged higher than the average answer for
questions 4, 5, 12, 14, and 18. The
responses separated by gender can be seen in Figure 12.
The participants in the 45-54 years old group had answers that
were at least 0.4 higher
than the average for questions 2, 3, 4, 5, 8, 9, 14, and 15. The
participants in this age group had
answers at least 0.4 less than the average for questions 12 and
16. The participants over the age
of 45 were far less accepting of having biometrics stored in a
government database to be used for
homeland security or law enforcement with answers at least 0.9
less than the average for
question 12 which was 35-55% lower scores than the
participants between 25-44 years old. The
participants over the age of 65 years old had answers that were
less than the average answer with
the exception of questions number 10 and 19 which were 0.3
and 0.1 more than the average. The

overall average of all of the answers from participants over the
age of 65 years old was 2.7. The
average for the other age groups were at least 0.6 higher with
most being 0.9 higher. The three
age groups between 25-54 years old all had overall averages of
3.6. The responses separated by
age group can be seen in Figure 13.
Figure
12: Impact of Gender on Biometrics Acceptance
Figure
13: Impact of Age on Biometrics Acceptance
Impact of Experience with Biometrics
Those participants that were very experienced with biometrics
had answers that were
higher than the average answer for questions 1, 2, and 4 relating
to logging into a computer,

boarding flights and using ATMs. Additionally, the very
experienced participants had scores
that were 0.4 higher than the average answer for question 5 and
19 relating to iris scans and
convenience features. Very experienced participants had scores
that were 0.9 higher than the
average for question 17 relating to unannounced biometrics than
the other participants. Likewise
very experienced participants had answers that were 0.4 lower
than the average for question 15
related to using biometrics to replace passwords. The
participants with no experience with
biometrics had scores that were 0.5 less than the average answer
for questions 14 and 19 relating
to screening individuals at public events and convenience
features. On average participants with
no experience had answers less than the average score, but their
answers for questions 7, 8, and 9
were over 0.2 higher than the average. Participants with no
experience had an overall average
answer of 3.4 which was less than the average answer of 3.6 for
both participants with some
experience and very experienced participants. The results
showing the responses based on

experience level are in Figure 14. Only 11% of the participants
were very experienced with
biometrics. 55% of the participants had some experience with
biometrics.
Figure
14: Impact of Experience on Biometrics Acceptance
Impact of Employment Status
Due to the low numbers of participants in the self-employed,
homemaker, and student
demographic subsets, their responses will not be used to
characterize opinions for the whole
subset. Military participants were about 10% less accepting of
vein pattern recognition than the
other participants and were 10% less convinced that biometrics
improve convenience. However,
they were about 20% more accepting of biometrics being stored
in a government database for
use in law enforcement or homeland security and were about
10% more accepting of biometrics
after being notified. Retired participants answered lower than

the average for all questions
except questions 9, 10, and 17. Retired participants were over
5% more accepting of vein pattern
recognition and 10% more accepting of transmitting
unencrypted biometrics. Retired
participants were least accepting of biometrics use with an
overall average answer of 3.2 and
military participants were most accepting with an overall
answer of 3.6. . The results showing
responses separated by employment status are in Figure 15.
Figure 15: Impact of Employment Status on Biometrics
Acceptance
Discussion
The survey reviewed and confirmed many of the assumptions
developed during the

literature review. Additionally, the survey was used to test the
nine hypotheses of the study. In
addition to the quantitative analysis of information, a
qualitative study was conducted to gather
information about the participants’ opinions that were not
constrained by the limitations of
quantitative questions. The qualitative results helped to support
and further emphasize the
results of the quantitative study.
Due to low numbers of participants in several demographic
categories, those categories
were not used for analysis within the demographics. However,
the results were factored into the
overall aggregate to be used for the average of all participants.
The categories that were not used
for the analysis of how education impacts biometrics acceptance
were Associate Degree and
some college, no degree due to low representation. For the
analysis of how different
employment categories impact acceptance of biometrics, the
categories of self-employed,
homemaker, and student were not specifically considered.
These categories were not used
because they had low representation and the researcher felt it

would be an inaccurate
characterization for the category if there were only one or two
participants due to the increased
impact of their responses. Also, while the qualitative results
were helpful to support the
quantitative results, some of the answers were skewed due to
the participants misunderstanding
of the purpose of the questions. There were some answers that
did not belong with the question
such as locations when the question asked for situations.
Additionally, some answers were not
considered because the participants wrote, “same as above” or
“same as previous answer” which
would work if the researcher analyzed each participant’s
responses separately. However, due to
the aggregate nature of the responses for analysis, those types
of responses were not helpful
because the researcher had no way to reference the previous
answers.
Through the study and subsequent analysis it was determined
that education impacts the

acceptance of biometrics. Participants with Bachelor Degrees
had an average answer that was
almost 10% less for question number 13 than the average
answers from those with Masters
Degrees or Doctorate Degrees. Although all of the answers
were less than 1.5, indicating
disproval, the results indicate that those participants with higher
degrees are more accepting of
the possibility of biometrics being used for targeted advertising
than the average participant. The
participants with Bachelor Degrees were at least 10% more
receptive than the average to using
biometrics for workplace accountability through clocking in and
for use by the government for
law enforcement or homeland security. Likewise, those with
higher degrees were between 5%
and 22% less accepting of biometrics for those purposes.
Additionally, those participants with
Bachelor Degrees were much more accepting of fingerprint and
palm print biometrics than those
with higher degrees with more than 15% difference and an
average score of 4.5 out of a possible
5 indicating high levels of comfort. Those participants that had
higher degrees were less

accepting of biometrics than those that had lower degrees with
those participants with Bachelor
Degrees having a 13% higher average answer than those
participants with Doctorate degrees.
Conversely, experience with biometrics affects the acceptance
of the technology in the
opposite way. Those participants that were very experienced
with biometrics were more
accepting of the technology than those with less experience.
The very experienced participants
were 22% more accepting of unannounced biometrics than those
with less experience.
Additionally, the very experienced participants were more
accepting of using biometrics for
logging into computers, boarding flights, using ATMs and were
over 10% more comfortable of
iris scans than the other participants. However, the experienced
participants were 10% less
accepting of using biometrics to replace passwords.
Participants with no biometrics experience
were less accepting of biometrics than those with some
experience or those that were very

experienced with an overall average answer that was 5% less
than the other two groups. This
aligns with the research by Riley et al. that describes the
relationship of familiarity with
biometrics and acceptance of the technology (2004).
Surprisingly, the participants with no
biometrics experience were over 5% more accepting of palm
print, facial scan, and vein pattern
recognition modalities than the overall average. However, they
were over 10% less accepting of
using biometrics for screening individuals at public events and
were less convinced that
biometrics improve convenience than those participants with
some or a lot of experience with
biometrics.
The biometric modality being used also has an impact on
acceptance. The more
traditional biometric modalities of fingerprint scan and palm
print scan were determined to be
more acceptable by the participants with average answers of 4.2
and 4.1 respectively. These
modalities have an average answer between 12.5% and 22.5%
higher than the other modalities of

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