Information technology — Biometric presentation attack detection — Part 3: Testing and reporting

ISO/IEC 30107-3:2017 establishes: - principles and methods for performance assessment of presentation attack detection mechanisms; - reporting of testing results from evaluations of presentation attack detection mechanisms; - a classification of known attack types (in an informative annex). Outside the scope are: - standardization of specific PAD mechanisms; - detailed information about countermeasures (i.e. anti-spoofing techniques), algorithms, or sensors; - overall system-level security or vulnerability assessment. The attacks considered in this document take place at the sensor during presentation. Any other attacks are considered outside the scope of this document.

Technologies de l'information — Détection d'attaque de présentation en biométrie — Partie 3: Essais et rapports d'essai

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INTERNATIONAL ISO/IEC
STANDARD 30107-3
First edition
2017-09
Information technology — Biometric
presentation attack detection —
Part 3:
Testing and reporting
Technologies de l'information — Détection d'attaque de présentation
en biométrie —
Partie 3: Essais et rapports d'essai
Reference number
ISO/IEC 30107-3:2017(E)
©
ISO/IEC 2017

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ISO/IEC 30107-3:2017(E)

COPYRIGHT PROTECTED DOCUMENT
© ISO/IEC 2017, Published in Switzerland
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized otherwise in any form
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ii © ISO/IEC 2017 – All rights reserved

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ISO/IEC 30107-3:2017(E)

Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 Attack elements . 2
3.2 Metrics . 3
4 Abbreviated terms . 4
5 Conformance . 5
6 Presentation attack detection overview . 6
7 Levels of evaluation of PAD mechanisms . 6
7.1 Overview . 6
7.2 General principles of evaluation of PAD mechanisms . 7
7.3 PAD subsystem evaluation . 7
7.4 Data capture subsystem evaluation . 8
7.5 Full-system evaluation . 8
8 Artefact properties . 9
8.1 Properties of presentation attack instruments in biometric impostor attacks . 9
8.2 Properties of presentation attack instruments in biometric concealer attacks .10
8.3 Properties of synthesized biometric samples with abnormal characteristics .10
9 Considerations in non-conformant capture attempts of biometric characteristics .11
9.1 Methods of presentation.11
9.2 Methods of assessment .11
10 Artefact creation and usage in evaluations of PAD mechanisms .11
10.1 General .11
10.2 Artefact creation and preparation .12
10.3 Artefact usage .13
10.4 Iterative testing to identity effective artefacts .13
11 Process-dependent evaluation factors .13
11.1 Overview .13
11.2 Evaluating the enrolment process .14
11.3 Evaluating the verification process .14
11.4 Evaluating the identification process .14
11.5 Evaluating offline PAD mechanisms .15
12 Evaluation using Common Criteria framework .15
12.1 General .15
12.2 Common Criteria and biometrics .17
12.2.1 Overview .17
12.2.2 General evaluation aspects .17
12.2.3 Error rates in testing .17
12.2.4 PAD evaluation .18
12.2.5 Vulnerability assessment .18
13 Metrics for the evaluation of biometric systems with PAD mechanisms .19
13.1 General .19
13.2 Metrics for PAD subsystem evaluation .20
13.2.1 General.20
13.2.2 Classification metrics .20
13.2.3 Non-response metrics .21
13.2.4 Efficiency metrics .22
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ISO/IEC 30107-3:2017(E)

13.2.5 Summary .22
13.3 Metrics for data capture subsystem evaluation.22
13.3.1 General.22
13.3.2 Classification metrics .22
13.3.3 Non-response and capture metrics .22
13.3.4 Efficiency metrics .23
13.3.5 Summary .23
13.4 Metrics for full-system evaluation.23
13.4.1 General.23
13.4.2 Accuracy metrics . .23
13.4.3 Efficiency metrics .24
13.4.4 Summary .24
Annex A (informative) Classification of attack types .25
Annex B (informative) Examples of artefact species used in a PAD subsystem evaluation for
fingerprint capture devices .31
Bibliography .32
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ISO/IEC 30107-3:2017(E)

Foreword
ISO (the International Organization for Standardization) and IEC (the International Electrotechnical
Commission) form the specialized system for worldwide standardization. National bodies that are
members of ISO or IEC participate in the development of International Standards through technical
committees established by the respective organization to deal with particular fields of technical
activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international
organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the
work. In the field of information technology, ISO and IEC have established a joint technical committee,
ISO/IEC JTC 1.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for
the different types of document should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject
of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent
rights. Details of any patent rights identified during the development of the document will be in the
Introduction and/or on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to the
World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see the following
URL: www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/IEC JTC 1, Information technology, SC 37,
Biometrics.
A list of all parts in the ISO 30107 series can be found on the ISO website.
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ISO/IEC 30107-3:2017(E)

Introduction
The presentation of an artefact or of human characteristics to a biometric capture subsystem in a
fashion intended to interfere with system policy is referred to as a presentation attack. ISO/IEC 30107
(all parts) addresses techniques for the automated detection of presentation attacks. These techniques
are called presentation attack detection (PAD) mechanisms.
As is the case for biometric recognition, PAD mechanisms are subject to false positive and false negative
errors. False positive errors wrongly categorize bona fide presentations as attack presentations,
potentially flagging or inconveniencing legitimate users. False negative errors wrongly categorize
presentation attacks (also known as attack presentations) as bona fide presentations, potentially
resulting in a security breach.
Therefore, the decision to use a specific implementation of PAD will depend upon the requirements
of the application and consideration of the trade-offs with respect to security, evidence strength, and
efficiency.
The purpose of this document is as follows:
— to define terms related to biometric presentation attack detection testing and reporting, and
— to specify principles and methods of performance assessment of biometric presentation attack
detection, including metrics.
This document is directed at vendors or test labs seeking to conduct evaluations of PAD mechanisms.
Biometric performance testing terminology, practices, and methodologies for statistical analysis have
been standardized through ISO and Common Criteria. Metrics such as FAR, FRR, and FTE are widely
used to characterize biometric system performance. Biometric performance testing terminology,
practices, and methodologies for statistical analysis are only partially applicable to the evaluation of
PAD mechanisms due to significant, fundamental differences between biometric performance testing
concepts and PAD mechanism testing concepts. These differences can be categorized as follows:
a) Statistical significance
Biometric performance testing utilizes a statistically significant number of test subjects representative
of the targeted user group. Error rates are not expected to vary significantly when adding more test
subjects or using a completely different group. Generally, taking more measurements increases the
accuracy of the error rates.
In PAD testing, many biometric modalities can be attacked by a large or indeterminate number of
potential presentation attack instrument (PAI) species. In these cases, it is very difficult or even
impossible to have a comprehensive model of all possible presentation attack instruments. Hence, it
could be impossible to find a representative set of PAI species for the evaluation. Therefore, measured
error rates of one set of presentation attack instruments cannot be assumed to be applicable to a
different set.
PAI species present a source of systematic variation in a test. Different PAI may have significantly
different error rates. Additionally, within any given PAI species, there will be random variation across
instances of the PAI series. The number of presentations required for a statistically significant test
will scale linearly with the number of PAI species of interest. Within each PAI species, the uncertainty
associated with a PAD error rate estimate will depend on the number of artefacts tested and the number
of individuals.
EXAMPLE 1 In fingerprint biometrics, many potent artefact materials are known, but any material or material
mixture that can present fingerprint features to a biometric sensor is a possible candidate. Since artefact
properties such as age, thickness, moisture, temperature, mixture rates, and manufacturing practices can
have a significant influence on the output of the PAD mechanism, it is easy to define tens of thousands of PAI
species using current materials. Hundreds of thousands of presentations would be needed for a proper statistical
analysis – even then, resulting error rates could not be transferred to the next set of new materials.
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ISO/IEC 30107-3:2017(E)

b) Comparability of test results across systems
In biometric performance testing, application-specific error rates based on the same corpus of biometric
samples can be used to compare different biometric systems or different configurations. The meaning
of “better” and “worse” is generally understood.
By contrast, when using error rates to benchmark PAD mechanisms, terms such as “better” can be
highly dependent on the intended application.
EXAMPLE 2 In a given testing scenario with 10 PAI species (presented 100 times), System detects 90 % of
1
attack presentations and System detects 85 %. System detects all presentations for 9 PAI species but fails to
2 1
detect all presentations with the 10th PAI species. System detects 85 % of all PAI species. Which is better? In a
2
security analysis, System would be worse than System , because revealing the 10th PAI species would orient an
1 2
attacker such that he could use this method to defeat the capture device all the time. However, if attackers could
be prevented from using the 10th PAI species, System would be better than System , because individual rates
1 2
indicate that it is possible to overcome System with all PAI species.
2
c) Cooperation
Many biometric performance tests address applications such as access control in which subjects
are cooperative. Errors due to incorrect operation are an issue of a lack of knowledge, experience
or guidance rather than intent. Significant uncooperative behaviour in a group is not part of the
underlying “biometric model” and would render the determined error rates almost useless for biometric
performance testing.
PAD tests include subjects whose behaviour is not cooperative. Attackers will try to find and exploit any
weakness of the biometric system, circumventing or manipulating its intended operation. Presentation
attack types, based on the experience and knowledge of the tester, can change the success rates for an
attack dramatically. Hence, it can be difficult to define testing procedures that measure error rates in a
fashion representative of cooperative behaviour.
d) Automated testing
In biometric performance testing, it is often possible to test comparison algorithms using databases
from devices or sensors of similar quality. Performance can be measured in a technology evaluation
using previously collected corpuses of samples as specified in ISO/IEC 19795-1.
In PAD testing, data from the biometric sensor (e.g. digitized fingerprint images) may be insufficient
to conduct evaluations. Biometric systems with PAD mechanisms often contain additional sensors
to detect specific properties of a biometric characteristic. Hence, a database previously collected for
a specific biometric system or configuration may not be suitable for another biometric system or
configuration. Even slight changes in the hardware or software could make earlier measurements
useless. It is generally impractical to store multivariate synchronized PAD signals and replay them in
automated testing. Therefore, automated testing is often not an option for testing and evaluating PAD
mechanisms.
e) Quality and performance
In biometric performance testing, performance is usually linked directly to biometric data quality.
Low-quality samples generally result in higher error rates while a test with only high-quality samples
will generally result in lower error rates. Hence, quality metrics are often used to improve performance
(dependent on the application).
In PAD testing, even though low biometric quality can cause an artefact to be unsuccessful, there is no
reason to assume a certain quality level from artefacts in general. Samples from artefacts can exhibit
better quality than samples from human biometric characteristics. Absent a model of attacker skill,
it seems valid (at least in a security evaluation) to assume a “worst case” scenario where the attacker
always uses the best possible quality. That way, one can at least determine a guaranteed minimal
detection rate for the specific test set while reducing the number of necessary tests at the same time.
It is then a matter of rating the attack potential of successful artefacts (effort and expertise for the
needed quality) in order to assess the security level, as is the practice in Common Criteria evaluations.
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ISO/IEC 30107-3:2017(E)

Based on the differences a) through e), the following general comments regarding error rates and
metrics related to PAD mechanisms can be derived:
— In an evaluation, PAI species are analysed/rated separately.
— Attack presentation classification error rates other than 0 % for a PAI species only prove that the PAI
can be successful. A different tester might achieve a higher or lower attack presentation classification
error rate. Further, training to identify the relevant material and presentation parameters could
increase the attack presentation classification error rate for this PAI species. The experience and
knowledge of the tester, as well as the availability of the necessary resources, are significant factors
in PAD testing and are taken into account when conducting comparisons or performance analysis.
— Error rates for PAD mechanisms are determined by the specific context of the given PAD
mechanism, the set of PAI species, the application, the test approach, and the tester. Error rates
for PAD mechanisms are not necessarily comparable across similar tests, and error rates for PAD
mechanisms are not necessarily reproducible by different test laboratories.
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INTERNATIONAL STANDARD ISO/IEC 30107-3:2017(E)
Information technology — Biometric presentation attack
detection —
Part 3:
Testing and reporting
1 Scope
This document establishes:
— principles and methods for performance assessment of presentation attack detection mechanisms;
— reporting of testing results from evaluations of presentation attack detection mechanisms;
— a classification of known attack types (in an informative annex).
Outside the scope are:
— standardization of specific PAD mechanisms;
— detailed information about countermeasures (i.e. anti-spoofing techniques), algorithms, or sensors;
— overall system-level security or vulnerability assessment.
The attacks considered in this document take place at the sensor during presentation. Any other attacks
are considered outside the scope of this document.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO/IEC 2382-37, Information technology — Vocabulary — Part 37: Biometrics
ISO/IEC 19795-1:2006, Information technology — Biometric performance testing and reporting — Part 1:
Principles and framework
ISO/IEC 30107-1:2016, Information technology — Biometric presentation attack detection — Part 1:
Framework
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/IEC 2382-37 and
ISO/IEC 30107-1 and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— IEC Electropedia: available at http://www.electropedia.org/
— ISO Online browsing platform: available at http://www.iso.org/obp
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ISO/IEC 30107-3:2017(E)

3.1 Attack elements
3.1.1
presentation attack
attack presentation
presentation to the biometric data capture subsystem with the goal of interfering with the operation of
the biometric system
Note 1 to entry: An attack presentation might be a single attempt, a multi-attempt transaction, or some other
type of interaction with a subsystem.
3.1.2
bona fide presentation
interaction of the biometric capture subject and the biometric data capture subsystem in the fashion
intended by the policy of the biometric system
Note 1 to entry: Bona fide is analogous to normal or routine, when referring to a bona fide presentation.
Note 2 to entry: Bona fide presentations can include those in which the user has a low level of training or
skill. Bona fide presentations encompass the totality of good-faith presentations to a biometric data capture
subsystem.
3.1.3
attack type
element and characteristic of a presentation attack, including PAI species, concealer or impostor attack,
degree of supervision, and method of interaction with the capture device
3.1.4
test approach
totality of considerations and factors involved in PAD evaluation
Note 1 to entry: Elements of a test approach are given in Clauses 7 to 11.
Note 2 to entry: A test approach refers to all processes, factors, and aspects specified in the course of the
evaluation.
3.1.5
item under test
IUT
implementation that is the object of a test assertion or test case
Note 1 to entry: The IUT is the equivalent of TOE in Common Criteria evaluations.
3.1.6
PAI species
class of presentation attack instruments created using a common production method and based on
different biometric characteristics
EXAMPLE 1 A set of fake fingerprints all made in the same way with the same materials but with different
friction ridge patterns would constitute a PAI species.
EXAMPLE 2 A specific type of alteration made to the fingerprints of several data capture subjects would
constitute a PAI species.
Note 1 to entry: The term “recipe” is often used to refer to how to make a PAI species.
Note 2 to entry: Presentation attack instruments of the same species may have different success rates due to
variability in the production process.
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ISO/IEC 30107-3:2017(E)

3.1.7
PAI series
presentation attack instruments based on a common medium and production method and a single
biometric characteristic source
EXAMPLE A set of fake fingerprints all made in the same way w
...

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