Anton SSN Testimony

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Testimony before the House Committee on Ways and
Means Subcommittee on Social Security on


Protecting the Privacy of the Social Security Number
from Identity Theft


21 June 2007


Statement of
Ana I. Antón, Ph.D.


Associate Professor
North Carolina State University


Director
ThePrivacyPlace.Org


On Behalf of USACM (the US Public Policy Committee
of the Association for Computing Machinery)










Introduction


Thank you Chairman McNulty and Ranking Member Johnson for the opportunity to
testify.


I am an associate professor at North Carolina State University in the Department of
Computer Science in the College of Engineering. I am the director of a privacy research
center named ThePrivacyPlace.Org, with collaborating faculty and students at NC State
University, Purdue University and Georgia Tech. In addition to my role as a faculty
member, I serve on several industry and government boards of technical advisors,
including the Department of Homeland Security’s Data Privacy and Integrity Advisory
Committee. A brief biography is in Appendix A.


This statement represents my own personal position as well as that of the Association for
Computing Machinery’s (ACM) Committee on U.S. Public Policy (USACM), of which I
am a member of its Executive Committee. ACM is a non-profit educational and scientific
computing society of more than 84,000 computer scientists, educators, senior managers,
and other computer professionals in government, industry, and academia, committed to
the open interchange of information concerning computing and related disciplines. The
Committee on U.S. Public Policy acts as the focal point for ACM’s interaction with the
U.S. Congress and government organizations. It seeks to educate and assist policymakers
on legislative and regulatory matters of concern to the computing community.
(See http://www.acm.org and http://www.acm.org/usacm.)


My statement today highlights two key policy and technology issues:


First, the Social Security number (SSN) should not be used as an identifier or
authenticator.
Such conflicting uses of SSNs confuse the role of identity and
authentication, making the SSN valuable to for stealing someone’s identity or committing
fraud. Furthermore, because SSNs are so readily available, they are not an adequate
means of identification or authentication.


Second, steps must be taken to reduce the use and exposure of SSNs.
Reducing the
use of SSNs helps protect individual information. The display of SSNs on ID cards and in
public records should be prohibited, and SSNs should be redacted from existing public
records. From a technical standpoint, we should require government and private entities
to secure or encrypt records or documents containing SSNs in storage and during
transmission.


Overview


Identity theft is no longer a rare crime impacting few and escaping the general public’s
attention. Since 2003, more than 36 million Americans have had their identities stolen1
and since February 2005 over 155 million personal records2 have been compromised,
causing serious harm to those affected by these thefts and exposures. Massive data
breaches, such as last year’s stolen laptop containing the Social Security numbers (SSN)
of 28 million veterans, are increasingly commonplace and will soon cease to be frontpage
news. With increasing public awareness of this epidemic, Congressional attention
has followed, with no less than eight different committees conducting oversight hearings
and proposing numerous bills.


Identity theft is a form of fraud that depends on two different factors, 1) information
being improperly acquired, and 2) that information being used to facilitate fraud. The
improperly acquired information is the enabler, but it is the fraud that does the damage.


A number of factors enable identity theft, but two key ones stand out for this committee’s
consideration. First, the use of the SSN is so widespread that it is a de facto national
identification number. Businesses and government agencies collect the SSN to identify
and then authenticate individuals. This has made it the primary instrument for stealing an
individual’s identity or creating a “synthetic identity,” which is a new identity cobbled
together using personal information from several sources. It is the key that unlocks access
to credit, banking accounts and various other services for criminals.


Second, current computing technologies enable the collection, exchange, analysis, and
use of personal information on a scale unprecedented in the history of civilization. As
computing technology and storage continue to advance and become cheaper, and as more
uses are found for information about people, we can only expect these collection
activities to increase. Whereas paper records with personal information, including SSNs,
used to require some effort to find, copy and disseminate, the spread of inexpensive
computing technology has made it much easier to find, use and exploit such information
– for good and for bad. Moreover, SSNs provide a way to easily link data records that
should not be easily linkable –– a key point in enabling data theft. Reducing the use of
SSNs will make it more difficult for thieves to, for example, tie together medical and
investment records.


Collectively, these trends suggest that it is a critical time for Congress to act to strengthen
the privacy of Social Security numbers. The use of SSNs is widespread, and no amount
of technology or law can “put this genie back in the bottle.” We can, however, construct
sensible policies, combined with new business procedures, and deploy technology using
best practices for privacy protection. Such measures will help protect SSNs and move us
away from relying on them as the key to unlocking one’s identity.


In this testimony, I will touch on several issues that describe the nature of the privacy and
security problems with SSNs. I will then discuss alternative approaches to managing
identity and plausible technical solutions for protecting privacy. Finally, I will discuss
some recommendations for this committee to consider as it moves forward with efforts to
protect the privacy of SSNs.


Use as an Identifier and Authenticator


The U.S. government issues Social Security numbers to track taxes and benefits.
Originally, the number was connected only with the Social Security program. Over time,
governments and other entities have expanded the uses of the SSN. Issued to individuals
for nearly three quarters of a century, each SSN is intended to be a unique number that
people keep for life. The problem we face today stems from the fact that the SSN is so
convenient for tracking individuals across public and private records that it is often used
as both an identifier and an authenticator.


An identifier is a name or other label that can be used to uniquely select a particular
person within a specific group or context. For example, my SSN identifies me within the
group of U.S. Social Security participants. But someone who knows my SSN is not
necessarily me. Many other people in many contexts have valid access to my SSN.


Authentication
is the process of verifying that an identifier is valid and associated with a
particular identity. There are three traditional categories of authenticators: knowledgebased
(“what you know,” e.g., a password), object-based (“what you have,” e.g., an RFID
token or a driver’s license), and ID-based (“what you are,” e.g., a biometric such as a
fingerprint).3 There are strengths and weaknesses in each form of authenticator; these are
discussed in more detail in USACM’s short tutorial on authentication, attached as
Appendix B.


Companies and government agencies rely on the SSN as an identifier because it gives
them some added degree of precision when disambiguating individuals. For example,
when distinguishing between 20 different Sally Smiths in a database, the SSN is
presumed to be unique and indicates exactly one individual. This holds true whether Sally
enters her name as Sally Ann Smith, S. Smith, or uses her married name from one of
several marriages. Clearly, this identification role is valuable to ensure that records are
not mixed and duplicate records are not created. However, privacy problems ensue if
access to those same personal records are provided when someone claiming to be Sally
provides the SSN as an authenticator. Her family members, former college roommate and
professors, employer, banker, former spouses and others likely know her SSN. So does
anyone with access to Sally’s records at any organization that uses her SSN to identify
her out of all the other Sally Smiths.


From a technical standpoint, the problem with SSNs is that some entities are using them
as an identifier, others are using them as an authenticator, and yet others are using SSNs
as both an identifier and an authenticator.4 For example, professors applying for some
Federal grants via the Internet enter their social security numbers, last names, and a
password to identify themselves. In this case, the SSN is used as an identifier and the last
name as a form of secondary authentication. As another example, use of the SSN when
opening a bank account is as an identifier, to indicate who is responsible for taxes. As a
last example, if you call your credit card company to increase your credit limit they may
ask for your SSN to authenticate you. These conflicting uses confuse the role of identity
and authentication and thus make SSNs much more valuable for stealing someone’s
identity.


Remotely conducted business transactions that rely on the SSN as an identifier and
authenticator are particularly risky. If someone is contacting his brokerage via the phone
or Internet to purchase stock against a credit card, the brokerage needs to authenticate the
identity of the customer as the holder of the credit card and the brokerage account. The
customer also needs to authenticate that he is communicating with the real brokerage, and
not with a criminal seeking to steal his credit card information. Furthermore, the
authentication needs to be performed in a way that someone eavesdropping on the
transaction cannot then masquerade as either party for any other operation. Knowledge of
a SSN (or any other universal identifier) is not sufficient to reliably authenticate any party
in this transaction, but this use is commonplace.


Ubiquity of SSNs


SSNs are so widely used that they are a de facto national identifier. Commercial entities
and government agencies rely on their use, some states have them on driver’s licenses,
employers use them as medical plan IDs and employee IDs, and many colleges have long
used them as student IDs. (In recent years universities have moved away from the use of
SSNs). The military also uses SSNs as military serial numbers and has them exposed on
the Common Access Card that every member the military carries for identification5.


In testimony before Congress6 in 2004, the General Accounting Office found that an
estimated 42 million Medicare cards displayed entire 9-digit SSNs, as did approximately
8 million Department of Defense (DOD) insurance cards and 7 million Department of
Veterans Affairs (VA) beneficiary cards.


As we have moved from paper-based systems to digital ones, the exposure of SSNs has
increased. SSNs are often used as identifiers on public documents, such as property
deeds. Before the widespread use of digital technologies, databases and networking, these
documents represented little threat of being a source of large-scale identity theft.
However, now such documents are digitally scanned and incorporated into massive
databases often held by data brokers that share or sell this data. This facilitates identity
fraud in dealing with other organizations that use knowledge of the SSN as a form of
authentication. This secondary use and electronic transmission of this data creates an
array of opportunities for the data to be intercepted and misused.


Data Security


Two weeks ago, before this subcommittee, Dr. Peter Neumann7 (an expert on privacy,
security and trustworthy computing issues) discussed the security and reliability
vulnerabilities of the existing computing infrastructure and the poor current state of
practice in building trustworthy systems. These vulnerabilities can and have led to the
exposure of personal information, particularly SSNs. Nearly two-thirds of the security
breaches from January 1, 2005 to June 11, 2007 resulted in the exposure of SSNs.8 (There
were more than 600 publicly reported data breaches during time period and, of these
breaches, more than 400 potentially exposed SSNs.9)


Creating complex systems that are dependably trustworthy (secure, reliable, survivable in
the face of many adversities) remains a grand challenge of computer science. Further,
because many of the privacy problems are related to total systems, encompassing
computers, communications, people, and procedures, they cannot be adequately protected
by technological approaches alone. While better computer security is a worthwhile
technical and policy goal, these factors suggest that a better approach is to move away
from reliance on SSNs – at the very least, to avoid depending on them as means of
authenticating identity.


Alternative Identifying Techniques


Reducing the use of SSN as both an authenticator and identifier will better protect
privacy and security; however, the question is, what other techniques can we use that
better protect identity?


A study by the American Journal of Public Health detailed the effectiveness of
combinations of data used as identifiers instead of the SSN10 It found the SSA National
Death Index could be used to identify people by certain data points (First Initial, Last
Name, Day of Birth, Month of Birth, and Year of Birth) as accurately with or without the
SSN. This means that adding the SSN falls within the margin of error when searching
with only the first initial, last name and birth year. Adding full name, full birth-date, and
possibly some other information such as birthplace would likely provide as complete and
unique identification as the SSN.


We should not, however, replace one enabler of ID theft with another. Many of these data
points are more readily available to strangers than SSNs. Thus, it is important that they
not be used to authenticate identity for anything of value. Clearly, context for
determining identity matters, but the larger issue is that we should move away from
reliance on any system that creates universal identifiers, and especially from systems that
use knowledge of those identifiers as authenticators of that same identity. It is more
secure to use multiple factors to confirm an individual’s identity. For data aggregators
looking for a universal identifier, it may be more convenient – perhaps even more
profitable – to work on ways to effectively sort and target their analyses to confirm that
the information they collect is appropriate for their intended uses.


Designing Systems to Protect SSNs


Databases containing personal information often employ the SSN as the “primary key” or
common identifier. This exacerbates the problems I have addressed as it presents yet
another vulnerability by making it easier to match records from disparate data sources.
Replacing SSNs as the primary key in these systems is not a large technical hurdle in
most cases. Random 9-digit numbers would work for virtually every company in the U.S.
and would not be difficult to generate. We can better protect individual privacy by using
different, random numbers in each company database. This would prevent someone from
easily correlating the personal data an individual held in several of those databases.


The technical challenge is in replacing the SSN in all those databases. First and foremost,
if an SSN is being used in a database as an index, then replacing it will require updating
the index. Indexes generally exist to make common selection operations faster in
databases. The worst-case scenario would be a database that has a great many
transactions per day and little to no downtime to update the index. For large, always-on
databases, replacing the SSN and updating the index can be a difficult process, but it is
possible.


The cost of cleaning up records in commercial databases is likely far from prohibitive for
all but the smallest of commercial entities. Usually smaller entities have less expertise,
time and money to scrub their records of SSNs. But, the smaller entities are also the least
attractive targets for identity theft.


The most vulnerable databases are employee records, which are typically not as secure as
other business databases both because of insider threat and because they are often
overlooked in audits of business assets.11


Universities are increasingly discontinuing the use and storage of SSNs whenever
possible, replacing them with university-specific ID numbers (i.e., a random 9-digit
identifier that is not the SSN). In cases where SSNs must be collected and stored (e.g., for
employment and financial aid), the SSN is no longer being maintained as the common
identifier or primary key. In addition, universities are actively adopting technologies to
protect SSNs. For example, devices containing SSNs are being protected by a passwordbased
security system using encryption. This voluntary approach can serve as a model for
other industries in the U.S. to similarly move away from the use of SSNs as primary
identifiers.


Recommendations


There are several actions that can be taken to protect the privacy of SSNs. I present two
sets of recommendations. The first set of recommendations address the purposes for
which SSNs are used. The second addresses how SSNs are stored and transmitted.


Recommendations on the Purposes and Uses of SSNs


• No bank, credit agency, government agency, or other entity should verify the
identity of a person based on weak authenticators such as knowledge of an SSN or
mother’s maiden name. Instead, they should require stronger authentication of
identity when conducting business. Strong authentication can initially be provided
by a passport, military ID or license with a photograph.12 Once that is established,
a secondary authenticator such as a secret, shared password or PIN can be used
for subsequent transactions. While this requires additional effort, it provides extra
layers of security, and should help assure the public that the security and privacy
of their information is being taken seriously.


• Universities are voluntarily moving away from SSNs in an attempt to reduce their
liability under the Family Educational Right to Privacy Act (FERPA) if SSNs are
accidentally exposed. This has also led to improvement of their database security.
Congress should consider making private institutions financially liable in a
manner similar to universities: Consumers would have a civil right of action if
their SSNs or other personal information is collected or exposed without a valid
business need-to-know, whether intentionally or inadvertently.


• There should be no penalty or discrimination against someone who will not
provide an SSN when conducting business, except where required by law to
disclose that information. Moreover, entities that collect SSNs should provide
notice that there will be not be a penalty for withholding the SSN. Within this
context, it should be an unfair trade practice for private entities (e.g., utilities) to
penalize or refuse to transact business with someone who declines to provide an
SSN that is not required by law. Coupled with the previous recommendation, this
provides a strong incentive to move away from the SSN. It is also consistent with
advice from the Federal Trade Commission on protecting oneself from identity
theft.13


Recommendations for Protecting SSNs in Storage and During Transmission


• The display of SSNs on ID cards and in public records should be prohibited.
Further, SSNs should be redacted from existing public records. Redacting SSNs
is, admittedly, complex because computers (and the Internet) are not good at
“forgetting” things. Once something is stored in a computer, erasing it
everywhere it is stored is difficult.


The National Security Agency has posted guides14 on how to redact data, but the
reality is that redaction has a bad reputation as a workable solution. Paper
redaction techniques such as covering a name or diagram with a blackened area
do not work well in digital files. There are also so many different formats for
digital files that the techniques that do work are generally not portable among
formats. However, ChoicePoint, as one of its newly adopted business practices in
the wake of its landmark $16 million settlement for endangering the privacy of
over 160,000 consumers in 2005, is now redacting SSNs and other personal data
from the public records that it provides to its clients. This is a welcome
development and one that could be required at other companies, especially data
brokers and credit bureaus, as a matter of public policy.


There are other steps that can be taken to reduce the use and exposure of SSNs. They
include:


• Require transmission of records or documents to be secure or encrypted if they
contain SSNs and other personally identifiable information. Even basic Secure
Socket Layer (SSL) encryption would help reduce the incidence of exposure and
minimize the damage. SSL technology is readily available and is commonly used
by almost every reputable e-commerce site. Properly encrypted data is usually
protected even if it is stolen (e.g., on a laptop disk or thumb drive).


• Require electronic security for files and devices containing SSNs. Each instance
of access to SSNs in databases should be logged for audit purposes and require a
secure session. These measures insert a level of security and accountability into
the maintenance of these databases. With proper access controls (where
individuals who access the database are controlled, recorded, and their specific
access limited to a minimal number of records), individuals can be held
accountable for breaches and exposures of SSNs that can be traced to a specific
access of a database.


• Eliminate the SSN as primary key in databases containing SSNs. A primary key
uniquely identifies each record in a database table. Instead of using the SSN, the
primary key should be a unique number generated by the database management
system. Universities and other large institutions have made this transition, and
their example should be encouraged in other agencies, companies and
organizations.


• USACM has a set of recommendations for enhancing the security, privacy and
accuracy of personal data kept in databases. Those recommendations are attached
as Appendix C. We encourage the committee to consider how these might be
integrated and supported by any legislation crafted to protect SSNs and related
personal information held either by government or by private organizations.


Conclusion


The increasing incidence of identity theft and data breaches requires that all entities,
public and private, take steps to better protect information. Where this subcommittee can
help is in encouraging a reduction in the use of the SSN in commercial and government
transactions and in public records. The SSN is used much more than is necessary and the
ubiquitous presence of SSNs makes them ideal targets for identity theft. Because these
numbers are so readily available, they are not an adequate means of identification or
authentication as many consider them to be. Reducing the use of SSNs helps protect
individual information and encourages businesses, government and universities –– some
of which have already started to make changes –– to move towards other means of
identification. These alternate means in many cases can be as accurate, and more secure,
than using the SSN. Increased privacy and security is not only a public good, but may
make people more comfortable about conducting business online.


Acknowledgments


I am particularly grateful to Cameron Wilson (ACM Director of Public Policy), David
Bruggeman (ACM Public Policy Analyst), Eugene H. Spafford (USACM Chairman, and
Professor at Purdue University), Travis D. Breaux, Laurie A. Jones, Aaron K. Massey,
Paul N.H. Otto, and many other members of ACM and USACM for their generous help
in my preparing this testimony.


Appendix A – Biographical Information


Dr. Annie I. Antón is an Associate Professor of Software Engineering in the College of
Engineering at the North Carolina State University. She received her Ph.D. in Computer
Science in June of 1997 with a minor in Management and Public Policy from the College
of Computing at the Georgia Institute of Technology in Atlanta. Her thesis co-advisors
were Dr. Peter A. Freeman and Dr. Colin Potts. She received a BS in Information and
Computer Science with a minor in Technical and Business Communication in 1990 and
an MS in Information and Computer Science in 1992 (also from Georgia Tech). After
one year at the University of South Florida, Dr. Antón joined the computer science
department at NC State. She was awarded an NSF CAREER Award in 2000, named a
CRA Digital Government Fellow in 2002, nominated and selected for the 2004-2005
IDA/DARPA Defense Science Study Group, and received the CSO (Chief Security
Officer) Magazine "Woman of Influence in the Public Sector" award at the 2005
Executive Women's Forum. She is associate editor of IEEE Transactions on Software
Engineering, the cognitive issues area editor for the Requirements Engineering Journal,
and a member of the International Board of Referees for Computers & Security. She is a
member of the International Association of Privacy Professionals, a senior member of the
IEEE as well as a member of the ACM U.S. Public Policy Committee's Executive
Committee. Antón currently serves on several boards: the NSF Computer & Information
Science & Engineering Directorate Advisory Council, the Computing Research
Association's Board of Directors, the CRA-W Board, an Intel Corp. Advisory Board, the
Department of Homeland Security Data Privacy and Integrity Advisory Committee, the
Berkeley TRUST Center Distinguished Advisory Board, and the Georgia Tech Alumni
Association Board of Trustees. She is a former member of the Microsoft Research
University Relations Faculty Advisory Board and the Georgia Tech Advisory Board
(GTAB). Dr. Antón is director of ThePrivacyPlace.Org (http://theprivacyplace.org), and
co-director of the NC State Electronic Commerce Studio. Her URL is:
http://www.csc.ncsu.edu/faculty/anton.


About USACM


USACM is the U.S. Public Policy Committee of the Association for Computing
Machinery (ACM). USACM members include leading computer scientists, engineers,
and other professionals from industry, academia, and government.
(http://www.acm.org/usacm)


About ACM


ACM, the Association for Computing Machinery (http://www.acm.org), is an educational
and scientific society uniting the world’s computing educators, researchers and
professionals to inspire dialogue, share resources and address the field’s challenges.
ACM strengthens the profession’s collective voice through strong leadership, promotion
of the highest standards, and recognition of technical excellence. ACM supports the
professional growth of its members by providing opportunities for life-long learning,
career development, and professional networking.


Appendix B – Understanding Identity and Identification


USACM
The Public Policy Committee of ACM
Understanding Identity and Identification


Professionals who work with issues of security and control use some terms to precisely
describe access to resources and naming. These same terms have usage in general language,
but the words frequently are used imprecisely and even misleadingly. When describing
how security in information systems operate, and when formulating regulations or laws, it
is important that these terms are understood and used precisely.
The purpose of this short document is to describe these important terms for readers who
are not familiar with the more formal definitions. These related terms are identification,
authentication, and authorization. Related concepts include uniqueness and biometrics.


Terms


Identification is associating a distinguishing label (identifier) with something within a
specific group or context. You can identify someone by getting both their label and the
context of that label. An ID card can provide both the name (e.g. “John Smith”) and the
context (e.g., “licensed driver”). Identification can also occur by providing only the
context or group name, such as identifying oneself as a police officer, a student, a graduate
of West Point, or a member of Congress by wearing an appropriate badge, uniform, or
class ring. The reliability of an identification depends on the confidence that the
distinguishing label and context actually apply to the individual in question.


Note that even when identification is reliable – and it often is not – it does not imply
anything beyond being able to distinguish among items or people. Identification can be
used to determine if someone is a member of a group or not, or among members of the
group. If someone were to identify herself as “Snow White,” that is an identification if
she uses it consistently. In the context of a Halloween party or an Internet chat room,
that may be a logical label to adopt.


A key concept is that identification does not need to be a standard name. It can be a
nickname, a login, or a simple description, such as “I am the tallest one here” or “I am the
one with red hair.” Those are means to distinguish one person from another in a particular
group context.


People are most often identified in social situations by their names. In the United States,
these names are usually composed of a first (given) name, one or more middle names
(usually), and a last (family) name. In other countries, names may be a single word, or
everyone may have a common family or middle name.


Uniqueness is when multiple items do not have the same identifier. Human names are
seldom unique across a large enough population. For instance, there are many, many
people named “John Smith” in the USA. If we also consider ancestors, then there may be
even more individuals who have been associated with the same identifier (name).


We can further qualify an identifier to make it more specific and less likely to be a
duplicate of another identifier. For instance, someone could be “John Smith who was born
April 1, 1952 in Boise and whose mother was named Matilda.” However, we cannot
always be certain this is unique, and it is unwieldy to use in formal documents. Thus, we
commonly use an artificial identifier that is generated and assigned in a manner that
ensures that it is unique within context. For instance, Social Security numbers are
supposed to be assigned without reuse, making them theoretically unique. Other
identifiers (e.g., driver’s license numbers) are similarly generated to provide uniqueness.


Authentication
is the process of verifying – to some desired level of confidence – that a
claimed identifier is valid and actually associated with a particular item or person. Often,
this validation is performed by one or more persons inspecting the identification and
authenticator(s). The authenticators can also be examined by some technical means, such
as a login program or a badge reader connected to a computer.


Authenticators of people are typically some combination of “something known,”
“something possessed,” and “something about (structural)” the person. These items have
been previously registered with the persons or organizations performing the
authentication. Additional factors can also be used, such as physical location, recognition
by human or canine guards, and so on.


Something known is a secret or a fact that is unlikely to be known to an impostor.
Passwords, when properly chosen and protected, are this form of authenticator.
In many old combat movies, the spy is exposed because he doesn’t know which
team won the World Series the previous year – this is another form of “something
known” as a group authenticator. Many companies use items such as “mother’s
maiden name,” “birth date” or “social security number” as authenticators, but this
is bad practice as those items are often easily discovered facts: Many of these
items are public information as a matter of law or custom.
Something possessed is a distinguishable token or a key that matches a counterpart.
A license issued by a government agency is a form of token. Another example
from an old movie is the dollar bill or playing card that is ripped raggedly in half –
the two halves are kept and joined together to mutually authenticate two parties.
Something about (structure) the object or person being authenticated. We can
examine something physical about the person we wish to identify, such as a
fingerprint, or the pattern of blood vessels inside the eye. If the comparison of a
person’s distinguished characteristic is automated, then it is known as a biometric.
A current location may also be used for authentication, such as GPS coordinates,
telephone caller-id or computer network address.

Using a combination of authenticators is known as multi-factor authentication.


Authorization is the granting of rights (verb) or the grant itself (noun). Generally, one
authorizes an authenticated party. Permission is used by some people as a synonym for
authorization.


An example
Consider a scenario involving a person who wishes to enter a guarded building. When the
person approaches the building to enter, a guard stops him to verify that he can enter.
The person produces an identification card (something possessed) issued by a trusted
authority (the context). The guard compares the picture on the ID with the face of the
person, and causes him to put his fingers on a scanner (a biometric). These checks confirm
that the person is the one identified by the card. She has been instructed that anyone with
a valid blue card is allowed to enter, but without a cell phone, so she allows the person to
pass after determining that he does not have a cell phone.


Note that this is use of multi-factor authentication, and the identification is based on
group membership (“people with a valid blue badge”) – no specific name or ID number is
required. Permission to enter is the authorization involved. A further element of access
control that is not based on identity or authentication is also involved: there is no
authorization to carry a cell phone in.


There are many potential weaknesses in this system as described. The system can be
redesigned to prevent the weaknesses, but defensive measures may be too expensive or
cumbersome to be worth the effort given both the likelihood of the threats occurring and
the value of what is behind the door. Examples of weaknesses include:


• The picture on the card may be old and the guard makes a false negative
authentication: she refuses to allow the authorized person to pass.


• The guard may be overpowered or bribed so that unauthorized people enter.


• The card has been altered from a valid card — the color has been changed, or the
original holder’s photograph and fingerprints have been replaced by this
impostor.


• The cards are made to published standards without adequate safeguards: this is a
forged card made by a well-informed and sophisticated attacker.


• The attacker has stolen the card, disguised himself as the cardholder, and donned
fingerprint caps that fool the scanning machinery.


• The guard is unable to recognize a disguised cell phone.


• Someone pretending to be a law enforcement officer, in uniform, orders the
guard to let him pass or he will arrest her for obstructing justice. She complies.


• If too many people arrive in a short time, the guard may not be able to process
them in a timely fashion, and someone is either denied access incorrectly or slips
in unnoticed.


• The guard may fall ill and leave her post, leaving the door locked or unlocked for
subsequent visitors.


• A first-time visitor has no way of knowing that this is really a legitimate guard
and the right door!


Additional Notes


1. As illustrated by the last point in the previous example, the problem of authentication
is bidirectional — all parties in the transaction need some level of assurance that they
know the identities of the other parties. This is one reason why phishing succeeds:
the customers enter their authenticating information, but the other party (the
purported merchant) is not strongly authenticated to the customer.


2. It is possible to have authentication and authorization without specific identification.
For instance, producing an authentic $20 bill provides authorization to make a
purchase for something up to $20 in cost. It is not a requirement to identify the
purchaser beyond being a member of the group who has cash.


3. Knowing precise, authentic identity does not disclose intent! Knowing the name of
everyone who enters a building or boards a plane does not mean that they will be
well-behaved. Mohamed Atta’s Florida driver’s license and picture were legitimate
and examined when he passed through airport security on 9/11/2001. Most
identification checks instituted in the wake of 9/11 perform at most a weak security
function because there is poor (or no) authentication, and even when the identity is
known it does not prove anything about intent.


4. Social security numbers are not supposed to be reused. However, numerous recorded
cases of SSN duplication make the use of these numbers as unique IDs problematic.


5. Most biometrics have been developed and tested for authentication of a claimed
identity, not for performing the identification itself; fingerprints are a notable
exception. Insufficient experience has been gained with both physical features and
biometrics to know error rates over large populations. By example, given the data that
John Smith is 6’1” tall, has brown hair and green eyes, we can determine with some
confidence whether a person in the room claiming to be John is actually John.
However, given that same information and a crowd of people in a football stadium, we
cannot be certain that we can uniquely identify John if he is present. Almost
certainly, we will also make many false positive identifications. The same problems
may exist with automated biometrics such as measuring facial features or hand
geometry.


6. We know that every potential biometric has deficiencies. Not everyone has valid
fingerprints over their entire lives, twins and triplets have the same DNA, and so on.
People with special interests in some technologies have made unsupported claims
about the performance of certain biometrics.


7. Most organizations use weak authenticators. In part, this is because most people are
poor at remembering items such as long passwords and multiple ID numbers. As
noted, use of authenticators such as mother’s maiden name, social security number, or
other such items is poor practice because those items can be easily found for many
people.


8. Every instance where identifiers and authenticators are to be used should be carefully
analyzed to determine strengths and weaknesses. This includes the value of what is
being protected, and the consequences of false positives (authenticating an incorrect
identity) and false negatives (failing to authenticate a valid identity).


9. As noted, identification and authentication mechanisms depend on context. Any
security protocol is only as strong as the weakest element.


Appendix C – Privacy Policy Recommendations

USACM
The Public Policy Committee of ACM
Policy Recommendations on Privacy
June 2006

BACKGROUND


Current computing technologies enable the collection, exchange, analysis, and use of
personal information on a scale unprecedented in the history of civilization. These
technologies, which are widely used by many types of organizations, allow for massive
storage, aggregation, analysis, and dissemination of data. Advanced capabilities for
surveillance and data matching/mining are being applied to everything from product
marketing to national security.


Despite the intended benefits of using these technologies, there are also significant
concerns about their potential for negative impact on personal privacy. Well-publicized
instances of personal data exposures and misuse have demonstrated some of the
challenges in the adequate protection of privacy. Personal data — including copies of
video, audio, and other surveillance — needs to be collected, stored, and managed
appropriately throughout every stage of its use by all involved parties. Protecting privacy,
however, requires more than simply ensuring effective information security.


The U.S. Public Policy Committee of the Association for Computing Machinery
(USACM) advocates a proactive approach to privacy policy by both government and
private sector organizations. We urge public and private policy makers to embrace the
following recommendations when developing systems that make use of personal
information. These recommendations should also be central to any development of any
legislation, regulations, international agreements, and internal policies that govern how
personal information is stored and managed. Striking a balance between individual
privacy rights and valid government and commercial needs is a complex task for
technologists and policy makers, but one of vital importance. For this reason, USACM
has developed the following recommendations on this important issue.


RECOMMENDATIONS


MINIMIZATION

1. Collect and use only the personal information that is strictly required for the
purposes stated in the privacy policy.
2. Store information for only as long as it is needed for the stated purposes.
3. If the information is collected for statistical purposes, delete the personal
information after the statistics have been calculated and verified.
4. Implement systematic mechanisms to evaluate, reduce, and destroy unneeded and
stale personal information on a regular basis, rather than retaining it indefinitely.
5. Before deployment of new activities and technologies that might impact personal
privacy, carefully evaluate them for their necessity, effectiveness, and
proportionality: the least privacy-invasive alternatives should always be sought.


CONSENT

6. Unless legally exempt, require each individual's explicit, informed consent to
collect or share his or her personal information (opt-in); or clearly provide a
readily-accessible mechanism for individuals to cause prompt cessation of the
sharing of their personal information, including when appropriate, the deletion of
that information (opt-out). (NB: The advantages and disadvantages of these two
approaches will depend on the particular application and relevant regulations.)
7. Whether opt-in or opt-out, require informed consent by the individual before
using personal information for any purposes not stated in the privacy policy that
was in force at the time of collection of that information.


OPENNESS

8. Whenever any personal information is collected, explicitly state the precise
purpose for the collection and all the ways that the information might be used,
including any plans to share it with other parties.
9. Be explicit about the default usage of information: whether it will only be used by
explicit request (opt-in), or if it will be used until a request is made to discontinue
that use (opt-out).
10. Explicitly state how long this information will be stored and used, consistent with
the "Minimization" principle.
11. Make these privacy policy statements clear, concise, and conspicuous to those
responsible for deciding whether and how to provide the data.
12. Avoid arbitrary, frequent, or undisclosed modification of these policy statements.
13. Communicate these policies to individuals whose data is being collected, unless
legally exempted from doing so.


ACCESS

14. Establish and support an individual's right to inspect and make corrections to her
or his stored personal information, unless legally exempted from doing so.
15. Provide mechanisms to allow individuals to determine with which parties their
information has been shared, and for what purposes, unless legally exempted from
doing so.
16. Provide clear, accessible details about how to contact someone appropriate to
obtain additional information or to resolve problems relating to stored personal
information.


ACCURACY

17. Ensure that personal information is sufficiently accurate and up-to-date for the
intended purposes.
18. Ensure that all corrections are propagated in a timely manner to all parties that
have received or supplied the inaccurate data.


SECURITY

19. Use appropriate physical, administrative, and technical measures to maintain all
personal information securely and protect it against unauthorized and
inappropriate access or modification.
20. Apply security measures to all potential storage and transmission of the data,
including all electronic (portable storage, laptops, backup media), and physical
(printouts, microfiche) copies.


ACCOUNTABILITY

21. Promote accountability for how personal information is collected, maintained, and
shared.
22. Enforce adherence to privacy policies through such methods as audit logs, internal
reviews, independent audits, and sanctions for policy violations.
23. Maintain provenance — information regarding the sources and history of personal
data — for at least as long as the data itself is stored.
24. Ensure that the parties most able to mitigate potential privacy risks and privacy
violation incidents are trained, authorized, equipped, and motivated to do so.


USACM does not accept the view that individual privacy must typically be sacrificed to
achieve effective implementation of systems, nor do we accept that cost reduction is
always a sufficient reason to reduce privacy protections. Computing options are available
today for meeting many private sector and government needs while fully embracing the
recommendations described above. These include the use of de-identified data,
aggregated data, limited datasets, and narrowly defined and fully audited queries and
searches. New technologies are being investigated and developed that can further protect
privacy. USACM can assist policy-makers in identifying experts and applicable
technologies.



_______________

1 Javelin Strategy and Research, "2006 Identity Fraud Survey Report", January 2006,
http://bbb.org/Alerts/article.asp?ID=651 and Javelin Strategy and Research “2007 Identity Fraud Survey
Report, data obtained from Privacy Rights Clearinghouse, “How Many Identity Theft Victims Are There?
What Is the Impact on Victims?”, accessed June 12, 2007,
http://www.privacyrights.org/ar/idtheftsurveys.htm


2 Privacy Rights Clearinghouse, "A Chronology of Data Breaches", accessed June 12, 2007,
http://privacyrights.org/ar/ChronDataBreaches.htm.

3 O’Gorman, L. Comparing Passwords, Tokens, and Biometrics for User Authentication. Proceedings of
the IEEE, Volume 91, pp. 2021-2040, 2003.

4 S.L. Garfinkel. Risks of social security numbers. Communications of the ACM 38(10), pp. 146, October
1995.


5 B. Acohido & J. Swartz. “Military Personnel Prime Targets for ID Theft,” USA Today, June 15, 2007,
accessed June 18, 2007, http://www.usatoday.com/tech/news/computersecurity/infotheft/2007-06-14-
military-id-thefts_N.htm?csp=34.


6 Government Accountability Office, “Social Security Numbers: More Could Be Done to Protect SSNs”,
March 20, 2006, http://www.gao.gov/new.items/d06586t.pdf

7 Testimony of Peter G. Neumann For the Congress of the United States House of Representatives
Committee on Ways and Means Subcommittee on Social Security Thursday, June 7, 2007,
http://www.acm.org/usacm/PDF/EEVS_Testimony_Peter_Neumann_USACM.pdf


8 Privacy Rights Clearinghouse, "A Chronology of Data Breaches", accessed June 12, 2007,
http://privacyrights.org/ar/ChronDataBreaches.htm.


9 Ibid.

10 B.C. Williams, L.B. Demitrack, and B.E. Fries. “The accuracy of the National Death Index when
personal identifiers other than Social Security number are used,” American Journal Public Health. 82(8):
1145-1147, August 1992.

13 Federal Trade Commission, “ID Theft: What’s It All About?”, June 2005.
http://www.ftc.gov/bcp/conline/pubs/credit/idtheftmini.pdf


14 See both http://www.fas.org/sgp/othergov/dod/nsa-redact.pdf and http://www.nsa.gov/snac/

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