Vulnerabilities of Biometric Authenticat

Abstract

Biometric systems have a powerful potential to provide security for a variety of applications, systems are nowadays being introduced in many applications and have already been deployed to protect personal computers, Banking machines, credit cards, electronic transactions, airports, high security institutions like nuclear facilities, Military Bases and other applications like borders control, access control, sensitive data protection and on-line tracking systems. While biometrics may improve security in different environments and serve many purposes, biometric systems, like any other security system, have vulnerabilities and are susceptible to threats. they are susceptible to external vulnerabilities of biometric systems so that their weaknesses can be found and useful countermeasures against foreseeable attacks can be developed The increasingly high profile use of biometrics for security purposes has provoked new interest in researching and exploring methods of attacking biometric systems.

Full text

Vulnerabilities of Biometric Authentication
“Threats and Countermeasures”
Abdulmonam Omar Alaswad
Ahlal H. Montaser
Fawzia Elhashmi Mohamad
Faculty of Information Technology
University of Tripoli
Faculty of Information Technology
University of Tripoli
Tripoli Faculty of Education
University of Tripoli
Tripoli - Libya
Tripoli - Libya
Tripoli - Libya
Email: a.laswad@it.uot.edu.ly
laswadmonem@yahoo.com
altuboli@hotmail.com
Fawz_hash@yahoo.com
Abstract:
Biometric systems have a powerful potential to provide security for a variety of applications, systems are nowadays being
introduced in many applications and have already been deployed to protect personal computers, Banking machines, credit
cards, electronic transactions, airports, high security institutions like nuclear facilities, Military Bases and other applications like
borders control, access control, sensitive data protection and on-line tracking systems. While biometrics may improve security
in different environments and serve many purposes, biometric systems, like any other security system, have vulnerabilities and
are susceptible to threats. they are susceptible to external vulnerabilities of biometric systems so that their weaknesses can be
found and useful countermeasures against foreseeable attacks can be developed The increasingly high profile use of biometrics
for security purposes has provoked new interest in researching and exploring methods of attacking biometric systems.
Keywords
Biometrics, Biometric Systems, Authentication, Verification, Vulnerabilities, attacks, Threats.
1. Introduction:
Biometrics technologies have been around for quite some time and many have been deployed for different
applications all around the world, ranging from small companies' time and attendance systems to access control
systems for nuclear facilities. Biometrics offer a reliable solution for the establishment of the distinctiveness of
identity based on "who an individual is", rather than what he or she knows or carries. Biometric Systems
automatically verify a person's identity based on his anatomical and behavioral characteristics. Biometric traits
represent a strong and undeviating link between a person and his identity, these traits cannot be easily lost or
forgotten or faked, since biometric systems require the user to be present at the time of authentication. Some
biometric systems are more reliable than others, yet they are neither secure nor accurate, all biometrics have their
strengths and weaknesses. Although some of these systems have shown reliability and solidarity, work still has to
be done to improve the quality of service they provide. In this work we present available standing biometric
systems showing their strengths and weaknesses and also presenting emerging technologies in which may have
great benefits for security applications in the near future.
Different biometric technologies are available in the market today that can be used for security. Biometric
technologies vary in their capabilities, performance and complexity. They can be used to verify or establish a
person’s identity and they all share several elements.
Biometric identification systems are essentially pattern recognition systems. They use acquisition scanning devices
and cameras to capture images, or measurements of an individual’s characteristics, and computer hardware and
software to extract, encode, store, and compare these characteristics. Usually this process is fully automated, which
makes decision-making very fast, in most cases, taking only a few seconds.
Depending on the application, biometric systems can be used in one of two modes: verification or identification.
Verification or also known as authentication is used to verify a person’s identity “to authenticate that people are
who they claim to be”. Identification is used to establish people’s identity “to determine who the people are”.
Although biometric technologies measure different characteristics in different ways, all biometric systems begin
with an enrollment process followed by a matching process which uses either verification or identification. It is
essential to keep in mind that the efficiency of security systems cannot be accomplished by relying on technology

alone. Technology and people must work together as part of an overall security process. Weaknesses in any of these
areas weaken the effectiveness of the security process. Leading biometric technologies include facial recognition,
fingerprint recognition, hand geometry, iris recognition, Retina recognition, and Signature recognition.
2. Attacks on Biometric
In this section of the paper we discuss biometric devices and systems vulnerabilities. We can group attacks on
biometric devices and systems into four categories:
2.1 Processing and Transmission Level Attacks
Though input-level attacks are an obvious illustration of biometric system vulnerability, attacks at the processing
and transmission level also deserve close attention.
As many biometric systems transmit sample data to local or remote workstations for processing, it is also
imperative that this transmission be secure, lest the transmission be intercepted, read, or altered. Most biometric
systems encrypt data in transit, but not all applications and devices lend themselves to encryption. Security
techniques such as encryption are often seen as deployer-specific aspects of system design.
Deployers need to assess the degree to which sample data might be exposed in transit or during storage, and they
need to define applicable system security techniques and best practices. Taken as a whole; anti-spoofing measures,
encryption of data in transmission, and applying appropriate fallback techniques are all critical aspects of biometric
system security. These techniques can be further enhanced through the introduction of multi-factor authentication
and randomization.
Multi-factor authentication can take two primary forms: the use of multiple biometrics or the use of biometrics in
conjunction with smart cards and PINs. Both methods reduce the likelihood of an imposter being authenticated.
Spoofing also becomes more time consuming and challenging when multiple body physiological or behavioral
characteristics need to be copied and imitated. Impostors for whom a biometric matches an enrolled user are
unlikely also to match with respect to a secondary biometric. Adding randomization to the equation also adds
security. Verification data, for example, could be randomized, such as asking for three fingerprints one day and a
different combination of two fingerprints the next day. Additionally, where time provides, designers of biometric
technologies and systems should explore random or cued challenges. That is, even if a person correctly
authenticates once, the system might still challenge the user to re-authenticate to help increase its confidence that
the biometric data submitted is genuine.
Cued challenges could also be paired with certain behaviors causing alarm – such as an uncommon stillness, lack
of movement, or change during the acquisition of biometric data. Technologies can still bear further development
and enhancement for monitoring and sensing micro-movement. Or perhaps aggressive challenges could be utilized
in conjunction with measurements of intelligent response time. For example, voice verification biometric systems
could measure the time it takes for a prospective entrant to read back a randomly generated pass phrase in order to
try to fight playback attacks pieced together from various recordings. If the response time exceeds a minimum
threshold or varies significantly from an average time captured over a series of sample submissions at enrollment,
the biometric system could issue a challenge and require recitation of a new pass phrase.
Finally, in conjunction with multi-factor authentication and randomization, vendors and researchers should explore
taking advantage of internal or subcutaneous characteristics. By focusing on biometric aspects that are difficult to
observe, capture, and duplicate covertly, security can thus be enhanced.
However, regardless of how well one tries to secure a biometric system, failures will inevitably occur. It is
therefore critical that attention not only be paid to preventing breaches, but also to handling breaches that have
occurred. A recently-publicized technique to mitigate the impact of certain system breaches is the concept of
cancelable biometrics. Cancelable biometrics solution uses algorithms to distort an image proffered and records the
distortion into its generated templates. The original image is never stored anywhere. The idea is that if a thief
steals the template with the distortion on it, that particular distortion can be eliminated from the list of access-
approved users, and the legitimate user can resubmit their original biometric data to generate a new distorted
template. As long as the algorithms that generate the distortions are carefully protected and ideally varied from
company to company or even system to system, this solution may be highly conducive to containment and
resolution of a breach. The solution, however, is not foolproof. If the original image is captured, it could
theoretically be re-enrolled to generate a new, distorted template.

2.2 Input Level Attacks
The primary input-level attacks, vulnerabilities at the point of sample acquisition and initial
processing, are spoofing and bypassing. While spoofing is the most frequently-cited input-level
vulnerability, other input-level vulnerabilities may be just as problematic, such as
“overloading.” “Overloading” is an attempt to defeat or circumvent a system by damaging the
input device or overwhelming it in the attempt to generate errors. This is also sometimes called
a buffer overflow attack for other security mechanisms. An example of this type of attack for a
biometric system would be the rapid flashing of bright lights against optical fingerprint sensors
or facial recognition capture devices can disrupt their proper functioning. Silicon sensors can
be easily damaged by short circuiting them or dousing them with water.
Because many biometric systems rely on sensitive equipment that can be overloaded relatively
easily, users may have opportunities to induce device or system failure. Systems must be
designed such that, if overwhelmed, basic functions must not fail. And when biometric devices
can no longer serve their intended function, fallback processes must be defined and enforced. A
person who causes a biometric system to fail may be doing so knowing that, as a consequence,
an unguarded door may be used as a temporary alternative means of entry. Security systems
must account for the potential functional failure of biometric systems and devices by means of
adequate backup measures.
2.3 Back-end Attacks
The previous two sections have described input level and transmission level attacks. Ensuring integrity and
protecting back-end subsystems is important in distributed biometric systems. Assuming that the back-end consists
of a matching subsystem, or a decision subsystem, or a combination of both attacks on the back-end will mainly be
targeted at modifying the matching or decision subsystem or compromising integrity of stored templates.
Attacking the template storage database is the most apparent type of back-end attack. The threat of unauthorized
modification or replacement of stored templates can result in false accepts or false rejects depending on the
motives of the attacker. If an attacker can find a way of injecting templates directly into the storage database then
the attacker could introduce him/her into the system without following the appropriate enrollment procedures. The
attacker could also hijack the identity of an authorized individual by replacing the original template with their own
template, thereby still preserving privileges linked to the authorized individual. If a template is compromised, it
could be reused in a replay attack. Although circumventing replay attacks addressed is addressed in the previous
section, compromise of stored templates is one of the most important threats that should be considered when
designing a distributed biometric system.
These kinds of attacks can be prevented by using encryption and data integrity (hashing) methodologies. Applying
common database security methodologies can also increase the level of difficulty for the attacker.
An attacker could modify or replace the matching subsystem or the decisions subsystem so that it gives an output
as desired by the attacker. This is a serious threat in a networked environment. The integrity of the sample is not
relevant in such an attack, and the authentication process can be compromised without attacking the input
subsystem or transmission process. This kind of an attack can be circumvented by applying security methodologies
like checking code integrity, and principles of building trusted systems.
A denial of service (DOS) attack targeted at the back-end subsystems is also a very realistic threat. Overloading the
processing units of the back-end subsystem with excess traffic could lead to unavailability of services. DOS attacks
have received a lot of attention in media over the last few years and it should be considered a very real threat to
biometric authentication systems also. Traffic analysis and traffic monitoring are commonly used methods to
thwart DOS attacks.
Along with technical threats, there are also policy related challenges that should be considered. Collusion between
a malicious attacker and enrollment center could allow the attacker to enroll in the system using a stolen or a false
identity. Although this threat is not focused only on the back-end subsystems, a properly formulated policy
involving the front-end and back-end subsystems should make such attacks harder to perpetrate.

2.4 Enrollment Attacks
The practical use of biometrics for E-Authentication is binding to one’s identity. Although the concept of an
Identity Management System lies outside the scope of this document, from a biometric enrollment standpoint
because of the essential binding requirement, the identity proofing process is a critical related function. Trust in
this process of vetting a person’s claimed identity, confidence in the validity of associated documents, and
reliability in the authenticity of issued electronic credentials taken together provide the very underpinning of
biometric based E- Authentication. Examples of threats to identity proofing include:
A .
Use of forged documents to verify a claimed identity.
B .
Collusion with corrupt personnel having system access and.
C .
Electronic attacks to impersonate legitimate system users and thereby gain electronic access to the ID
application, proofing process and issuance system.
The following Countermeasures can be taken against these Identity Proofing threats:

Enforced separation of roles and duties of those involved in the processing, approval
and credential issuance process.

Close inspection of documents for forgery or tampering and use of third party
substantiation; for example, use of written inquiries.

Electronic system security protection – strong access controls, data encryption,
firewalls etc.

Strong issuance controls which confirm the user at time of credential issuance and
which preclude manual modifications to personalization data.
Vulnerabilities during enrollment of a person’s biometrics such as fingerprints, iris and facial features include:
A .
Enrollment of a person’s valid biometric(s) with a created or substituted identity. In this scenario, a person
uses/enrolls their own biometrics under a false or assumed identity which subsequently allows that person to
gain unauthorized access to and conduct eCommerce transactions and other logical and/or physical assets such
as computers, networks, databases, applications and facilities.
B .
Enrollment of substituted or swapped biometrics (not their own) along with a valid identity which
subsequently can be used by a third party to masquerade and gain access to eCommerce systems and/or other
logical or physical assets.
C .
Enrollment of substituted or false biometrics (e.g. a “gummy bear fingerprint”) with a false or assumed
identity which can later be used to gain access to eCommerce systems and/or other logical or physical assets.
D .
Enrollee collusion with the enrollment operator. In this scenario, any of the above can be facilitated, as well
as, unauthorized entry of or modifications to system data records or input thereto.
E .
External based attacks against the Enrollment Station and/or other system components it communicates with.
Examples include spoofing, sniffed transmissions, Man-in-the- Middle, and Replay.
The following Countermeasures can be taken against these threats during Enrollment of Biometrics:

Observed enrollment of biometrics instead of un-observed self enrollment.

Identity check/confirmation of the applicant enrollee at time of enrollment.

Remote system and enrollment station network protection and access controls, secure point-to-point
encrypted communications channel(s).


Enrollment Station device level firewall, and detection systems of unauthorized
modifications to all relevant data records and electronic file systems.
Figure 1 - Attack points on a biometric system
3. Vulnerable points of biometric systems, Threats and Countermeasures.
Points of possible attacks are identified and shown in Figure 1, they fall into 4 categories as we have discussed
earlier, countermeasures are described below according to the specified categories
 Attacks during processing/interaction [Attack points 1, 3, 5, 9, 11],
Location
Threats
Countermeasures
1 Data Collection
Spoofing
•
Liveness detection
•
Challenge/response
Use of un-trusted device
(Device substitution)
•
Mutually authenticate/use symmetric key or
asymmetric key
Overloading/Flooding
(Denial of Service)
•
Rugged devices
3 Signal Processing
Insertion of imposter data
•
Use strong tested algorithms
Component replacement
•
Signed components
5 Matching
Insertion of imposter data
•
Use strong tested biometric algorithms
Component replacement
•
Signed components
Storage
Matching
Decision
Signal
Processing
Data
Collection
Verifier
1
2
3
5
4
6
8
10
9
11
Biometric
Enrollment
Identity
Proofing
12
13
7

“Guessing” (FAR attack)
•
Use strong tested biometric algorithms
•
1:1 matching
•
Multi-biometric/multi- factor
Manipulation of match scores
•
Debugger hostile environment
Hill-climbing
•
Coarse scoring
•
Trusted sensor (Mutual authentication)
•
Secure channel
9 Decision
Hill climbing attack
•
Coarse scores
•
Mutual Authentication
•
Secure channel
Manipulation of threshold
setting
•
Protected function (access control)
•
Data protection
Manipulation of match
decision
•
Debugger hostile environment
Component replacement
(“yes machine”)
•
Sign components
11 Application
(verifier)
Malicious code
•
Conform to standards (BioAPI, CBEFF)
•
Code signing
 Attacks on the biometric data when it is at rest (in memory or in storage)
[Attack points 1, 3, 5, 9, 11 “above” + 7 “below”].
7 Storage
Database compromise (reading
template, replacing template(s),
changing bindings)
•
Hardened server
•
DB access controls
•
Sign templates, Store encrypted templates
•
Store template on smart cards or other
device.
 Attacks between stages (when the biometric data is in transmission)
[Attack points 2, 4, 6, 8, 10].
Location
Threats
Countermeasures
2 Raw data
transmission
Eavesdropping attack
•
Transmit data over encrypted path/secure channel
Replay attack
•
Mutually authenticate/use symmetric key or
Asymmetric key
•
Digitally sign data
•
Utilize Timestamp/Time to Live (TTL) tag
Man in the middle attack
•
Bind biometric to PKI certificate
•
Transmit data over encrypted path/secure
channel
Brute force attack
•
Time out/lock out policies
4 Processed data
transmission
Eavesdropping attack
•
Transmit data over encrypted path/secure
channel
Replay attack
•
Mutually authenticate/use symmetric key or
asymmetric key
•
Digitally sign data
•
Utilize Timestamp/Time to Live (TTL) tag
Man in the middle attack
•
Bind biometric to PKI certificate
•
Transmit data over encrypted path/secure channel

Brute force attack
•
Time out/lock out policies
6 Template
retrieval
Eavesdropping attack
•
Transmit data over encrypted path/secure
channel
Replay attack
•
Mutually authenticate/use symmetric key or
asymmetric key
•
Digitally sign data
•
Utilize Timestamp/Time to Live (TTL) tag
Man in the middle attack
•
Bind biometric to PKI certificate
•
Transmit data over encrypted path/secure
channel
8 Matching score
transmission
Hill climbing attack
•
Coarse scores
•
Trusted sensor (Mutual authentication)
•
Secure channel
Manipulation of match score
•
Secure channel
•
Mutual authentication between matcher
and decision components
Component replacement
(“yes machine”)
•
Sign components
10 Communication
to application
Eavesdropping attack
•
Transmit data over encrypted path/secure channel
Manipulation of match
decision
•
Transmit data over encrypted path/secure
channel
 Attacks during enrollment of one’s biometrics and one’s confirmed identity
[Attack points 12 and 13].
Location
Threats
Countermeasures
12 Identity Proofing
Forged documents
Close document inspection for authenticity, alterations etc.
Independent inquiries and confirmation
Collusion/Corrupt processing
personnel
Separation of roles & duties, audit trails
Unauthorized electronic or
manual access to obtain, insert,
modify or change data input and
records
Strong system access controls,
firewalls, encryption of data, chain of custody for
records/modifications, protected storage repositories
13 Biometric
Enrollment
Valid enrolled biometric but
bound to false identity
Check of presented identity documents with those
submitted during identity proofing process.
Valid identity but bound to
false biometric(s)
Observed enrollment of biometrics
Unauthorized Access to
Enrollment Station(s) and/or
related data base
Network& Enrollment Station Access controls, protected
transmission links including data transiting, and enrolled
user data base protection l
4. CONCLUSIONS
Biometrics offers a valuable approach to extending current security technologies that make it far harder for fraud to
take place by preventing ready impersonation of the authorized user.
In using biometrics we must be aware of the fact that they are not measuring perfectly, and that many operational
factors may cause them to fail. In such cases administrative procedures to resolve operational failures may need to

be put in place to prevent adverse customer reaction, bad publicity and failures in public acceptability. Whilst these
failures may not represent a significant proportion of transactions they will have a ‘publicity’ effect that is far more
damaging to all the success gained by the service.
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