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AIT 672 > Week 5 - Biometrics and Access Control Basics > Flashcards

Week 5 - Biometrics and Access Control Basics Flashcards

1
Q

A personal characteristic of a Human Being that is used to verify and confirm the presence of that individual from a previous enrolled sample

A

biometric verification

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2
Q

A personal characteristic of a Human Being that is used to identify that individual in a population using a set of previously enrolled samples

A

biometric identification

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3
Q

physiological characteristics

A
  • Fingerprint
    - Iris patterns
    - Retinal Pattern
    - Facial features
    - Hand Geometry
    - DNA
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4
Q

Behavioral characteristics

A

traits that are learned or acquired, such as:

- Hand Signature
- Keystroke dynamics
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5
Q

Various biometric characteristics are called…

A

Modalities

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6
Q

Biometric Technologies using multiple characteristics are called…

A

Multimodal

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7
Q

Biometric Sample / Data

A

The unprocessed image or recording of a physiological or behavioral characteristic. Sample Types are:
Fingerprint: Fingerprint image
Voice recognition: Voice recording
Facial recognition: Facial Image
Iris recognition: Iris Image . Retina-scan: Retina Image
Hand geometry: 3-D image of top and sides of hand and fingers
Signature verification: Image of signature and record of related dynamics measurements
Keystroke biometrics: Recording of characters typed and record of related dynamics measurements

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8
Q

How does DNA differ as biometric

A

DNA requires a tangible physical sample as opposed to an impression, image, or recording.
DNA matching is not done in real-time, and currently not all stages of comparison are automated.
DNA matching does not employ templates or feature extraction, but rather represents the comparison of actual samples

Regardless of the above differences, DNA is a type of biometric inasmuch as it is the use of a physiological characteristic to verify or determine identity.

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9
Q

Acquisition Devices

A

Read, Scan or Collect Data about biological characteristic that is being measured. The output is called the Biometric Sample. (e.g., Fingerprint Sensors or scanners for gathering fingerprints)

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10
Q

Signal Processing Algorithms

A

Perform a series of quality control activities to improve the quality of the acquired biometric sample

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11
Q

Template Generators

A

Generate Templates with a standards-based or Proprietary template format using the in-built feature extraction algorithms

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12
Q

Matchers with Matching Algorithms

A

Compare templates generated from acquired samples (verification template) to existing templates in storage (enrollment template) to generate a score

Compare score against a chosen threshold (Configuration parameter) to arrive at a Match or No-Match decision

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13
Q

Chosen threshold for biometric matching

A

Configuration parameter

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14
Q

Enrollment Phase Processes

A

Enrollment Phase (Processes)
- User Submission - Data Capture (Acquisition)
- Image or Signal processing – Feature
Extraction
- Template Generation
- Standardized Templates

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15
Q

Determinants

A

Used to asses quality of samples

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16
Q

Design Determinant

A

Quality of Acquired Input Samples

   - Better Sensor Design
   - Better User Interface Design
   - Standards Compliance
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17
Q

Non-Design Determinant in Biometrics

A

Improve Quality of Analysis

    - Initiating Reacquisition from a user
    - Real-time selection of best Sample
    - Selective invocation of different processing methods
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18
Q

Feature Extraction

A

The automated process of locating and encoding distinctive characteristics from a biometric sample in order to generate a template

Closely held secret

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19
Q

Characteristics used in Feature Extraction include:

A

Fingerprint: Location and direction of ridge endings and ridge bifurcations on fingerprint (called Minutiae points)
Voice recognition: Frequency, cadence and duration of vocal pattern
Facial recognition: Relative position and shape of nose, position of cheekbones
Iris recognition:Furrows and striations in iris
Retina-scan: Blood vessel patterns on retina

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20
Q

Biometric Template

A

A comparatively small but highly distinctive file derived from the features of a user’s biometric sample or samples, used to perform biometric matches.

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21
Q

When is a template created?

A

A template is created after a biometric algorithm locates features in a biometric sample

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22
Q

Enrollment templates

A

created upon the user’s initial interaction with a biometric system, and are stored for usage in future biometric comparisons

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23
Q

Verification templates

A

generated during subsequent verification attempts, compared to the stored (enrollment) template, and generally discarded after the comparison

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24
Q

Biometric template interoperability

A

Biometric templates are not interoperable - a template generated in vendor A’s fingerprint system for a person may not match when compared to a template generated in vendor B’s fingerprint system for the same person.

To make the Templates interoperable, ANSI and ISO have developed Standardized formats for templates pertaining to various biometric characteristics.

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25
Q

Two processes in biometric data matching

A

Identification and Verification

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26
Q

Matching of a single live sample with large number (may be millions) of stored samples is called

A

Identification or 1-to-n or 1-to-many matching

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27
Q

Matching of a single live sample with a single stored sample is called

A

Verification or 1-to-1 matching

28
Q

Biometric Identification

A

The process of determining a person’s identity by performing matches against multiple biometric templates

Identification systems are designed to determine identity based solely on biometric information

There are two types of identification systems: positive identification and negative identification

29
Q

Positive Identification

A

Find a match for a user’s biometric information in a database of biometric information

30
Q

Negative Identification

A

Compares 1-to-Many but designed to ensure that a person is not present in a database

31
Q

Biometric Veification

A

The process of establishing the validity of a claimed identity by comparing a verification template to an enrollment template.

32
Q

Biometric Matching

A

Comparison between the match or verification template (created using submitted sample) with reference or enrollment template that is stored in the database to determine the degree of similarity or correlation

Results in score

33
Q

Threshold

A

The threshold is a pre-determined value that limits what is acceptable or not for a system

If the score exceeds the threshold, the result is a match;

When resource has low value, the threshold is set low

34
Q

Score

A

A number indicating the degree of similarity or correlation of a biometric match

35
Q

Technology Evaluation

A
  • Evaluates the performance of the underlying technology
  • Evaluates correct matching rates between a combination of Fingerprint Extractors and Fingerprint Matchers
  • Give a large sample of known matching pairs and see how well a matcher performs
36
Q

Scenario Evaluation

A

Assesses how well a biometric technology works under

a given scenario – Large number of human samples

37
Q

Biometric System Performance Metrics

A

False Match Rate (FMR)
False Non-Match Rate (FNMR)
Failure to Enroll (FTE) Rate

38
Q

False Match Rate (FMR)

A

The probability that a given user’s verification template will be incorrectly judged to be a match for a different user’s enrollment template.

Also referred to as false acceptance rate

Informally speaking a high FMR will get unauthorized persons IN instead of rejecting them

39
Q

False Non-Match Rate (FNMR)

A

The probability that a user’s verification template will be incorrectly judged to not match that same user’s enrollment template

Also referred to as false rejection rate

Keeps the Good Guy OUT

40
Q

Failure to Enroll (FTE) Rate

A

The probability that a given user will be unable to enroll in a biometric system due to insufficiently distinctive biometric sample(s) – Any sample collected does not meet the necessary quality criteria

41
Q

Correlation between Metrics

A

Decreasing the FMR, or making the system less susceptible to imposters, results in an increased likelihood that legitimate users will be rejected (FNMR)

Decreasing the FTE by allowing a higher percentage of subject to enroll successfully leads to higher FNMR, as users with low-quality biometric samples have an increased presence in the system.

42
Q

Biometric Data in PIV Program

A

Ten Fingerprints
Face Image
Images of two fingers (or Irises if not collectable)

43
Q

IMP-1

A

Combined plain impression of the four fingers on the right hand (no thumb)

44
Q

IMP-2

A

Combined plain impression of the four fingers on the left hand (no thumb)

45
Q

IMP-3

A

Combined impression of the two thumbs

46
Q

Confidentiality

A

refers to the need to keep information secure and private

47
Q

Integrity

A

refers to the concept of protecting information from being improperly altered or modified by unauthorized users

48
Q

Availability

A

refers to the notion that information is available for use when needed

49
Q

Every organization typically has a unique set of requirements that dictate the circumstances and conditions under which users are permitted access to resources. These requirements are called….

A

access control policies

50
Q

the third part of an access control system that uses a set of components that work together to bring about policy preserving access (or enforce access control policies) is called…

A

Access control mechanism

51
Q

Components of access control mechanism

A

include access control data for expressing policies and representing attributes, as well as a set of functions for tracking access requests, and for computing and enforcing access decisions over those requests in accordance with policies

52
Q

access control models

A

To facilitate building a robust access control mechanism, access control models are used as an intermediary between access control policies and mechanisms. Models help to define policies in a formal way without redundancies and contradictions.

53
Q

Authorizations are expressed using four basic notions

A

user, subject, operation and permission

54
Q

user

A

a person who interfaces with the computer system

55
Q

subject

A

A computer process acting on behalf of a user is referred to as a subject

56
Q

object

A

An object can be any resource accessible on a computer system – files, databases, individual records or devices such as printers.

57
Q

operation

A

An operation is an active process invoked by a subject (e.g., read, write). A subject can invoke multiple operations (deposit, withdraw in an ATM)

58
Q

Permissions

A

Permissions (or privileges) are rights to perform some operation on a given object.

59
Q

access control matrix

A

In an access control matrix, the state of an access control system is defined by the triple (S,O,A)

S – set of subjects, O – set of objects and A – access matrix

Rows correspond to subjects (S)
Columns correspond to objects (O)

Each matrix entry A[s,o] is a set of allowed operations (rights)

An access control matrix is an interesting construct but rarely implemented as such in an access control system due to: (a) for a system with large number of users and objects, matrix will become very large and (b) Matrix will be sparsely populated

60
Q

access control enforcement

A

The basic function of the access control system is to ensure that only the operations specified by the matrix can be enforced. This basic function is called access control enforcement.

61
Q

Access Control List (ACL)

A

In Object or Resource-centric representation (ACL) authorizations are expressed by attaching a list of authorized users and permitted operations (permissions) to each object/ resource.

62
Q

Capability List

A

In User or Subject-centric representation (Capability List) authorizations are expressed by attaching a list of objects/resources and allowed operations on those objects/resources for each user or subject. The list thus represents the complete capability possessed by the designated user or subject.

On the other hand, it is difficult to review the subjects that can access a particular object

63
Q

Biometric Enrollment Processes

A
  1. user submission - data capture
  2. image or signal processing - feature extraction
  3. Template Generation
  4. Matching phase
64
Q

Decreasing the FMR, or making the system less susceptible to imposters, results in

A

an increased likelihood that legitimate users will be rejected (FNMR)

65
Q

Decreasing the FTE by allowing a higher percentage of subject to enroll successfully leads to

A

higher FNMR, as users with low-quality biometric samples have an increased presence in the system.

AIT 672 (4 decks)

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