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Biometrics Week 2 Flashcards

1
Q

What is authentication?

A

Is the process of verifying or determining the user’s identity.
A natural recognition capability for human being.
Automated authentication assign the task of authentication to machine for greater security, efficiency, and convenience.

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2
Q

Authentication can be?

A

Verification: Am I who I claim I am?
Or
Identification: who am I? (for finding a “wolves in a sheep clothes”)

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3
Q

Authentication can be Based on Different Concepts:

A

Knowledge
Possession
Biometrics
Any combination of the three

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4
Q

Knowledge Based Authentication

A

Something you know:
a password, pass-phrase, PIN…
Works reliably if they are not easily guesses, disclosed…

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5
Q

Problem with Knowledge based Approach

A

Problem:
difficult to remember,
easily guessed by imposters
Can be stolen or forgotten
Can be shared: a limited degree of accountability with transferability of credentials.
More than 15% of people seem to write their PIN on their ATM card

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6
Q

Possession Based Authentication

A

Something you have:
identity document, a token, a key, a card,..
Solve some of the problems with knowledge-based authentication forms:
No need to remember password
A limited degree of accountability with transferability of credentials.
The owner can tell if the card or token is stolen

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7
Q

Problem with possession-based approach

A

Possession could be:
lost,
stolen
shared
misplaced
forgotten

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8
Q

Benefits of Biometrics

A

Convenient: nothing to lose or remember
Can’t be guessed, stolen, shared or lost
Non-repudiation: Links an access to a person, not to a password or a card.
Protects against identity theft
Higher perceived degree of security

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9
Q

Security Levels combos:

A

Know Have Are
Have Are
Know Have
Know

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10
Q

Major Factors Influencing the Adoption of Biometrics

A

Security

Higher security through non-repudiation

Can not be stolen/ easily reproduced/guessed

Convenience

Integral and distinctive part of human being

Set it up once and forget about it

Cost/Technology

Higher return on investment through higher protection

Drop in the price of biometric sensors

The underlying technology is becoming more mature

Products have attained higher level of accuracy and throughput

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11
Q

Why Convergence?

A

Streamlined Provisioning/de-Provisioning
Single Point of enrollment
Lowered risk of penetration
Ease of Use

Shared Credentials
Reduced Cost
Lowered risk of credential sharing

Common Security Policies
Improved Accountability
Better Audit capability
Policies commensurate with overall corporate objectives
Compliance with Regulatory Processes

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12
Q

Biometrics Based Authentication

A

Biometrics = bio (life) + metrics (to measure)
Deals with automated methods of verifying or recognizing living persons based on their:
Biological characteristics (e.g., face, fingerprint, iris, hand geometry, retina)
Behavioral characteristic (e.g., signature, gait)
Combined (e.g., Voice)
No human involved in the authentication process
Should be done in real-time

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13
Q

Criteria for a Biometric Solution to be Applied for Authentication

A

Universality or Availability
Every person should have the characteristic

Uniqueness or Distinctiveness
Different persons should have different characteristics
Also referred to as having the discriminatory power

Permanence or Robustness
The characteristic should be time invariant
Should not change with varying operating condition

Collectable or Accessibility
The characteristic should be measurable quantitatively within reasonable time frame

Performance
It should be practical to collect and measure, and it should give an acceptable identification rate.

Acceptability
Users should not have an objection to collect/measure

Circumvention
Should not be too easy to fool

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14
Q

Applications of Biometrics Systems

A

Forensics
Government
Commercial

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15
Q

Taxonomy of uses of Biometrics Systems

A

Positive identification
Verifies that the submitted sample is from an individual known to the system
exp. Access to a budlings, access to a mobile device,..

Negative identification
Exp. Verifies that the submitted sample is from an individual not known to the system
Exp. Uses for preventing duplicate in welfare.

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16
Q

Basic Functions of a Biometric System

A

Capture
The process of measuring the biometric characteristics of a person using a sensing device

Process
The process of converting the biometric feature into a numeric format (template) that can be stored into the database

Enrolment
Registering a biometric template of a person in a database

Identification
Finding the template in a database that matches the live template at hand.

Verification
One-to-one process: matching a live template against a single stored template

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17
Q

Voice

A

Different from speech recognition
Based on the analysis of voice patterns and characteristics such as pitch, tone,..
Voice signal is transformed and digitized
Speaker verification can be:
Text-dependent, text-independent, language independent, language dependent
Can be used for authentication over phone

Weaknesses
Background noise (airplanes)
Voice can be affected by the person’s health, emotion, …
It can be mimicked, recorded and re-played.
Lengthy enrollment
Attacks:
Tape recordings
Identical twins or people with sound-alike

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18
Q

Facial Recognition

A

A very natural process to human being
Analyze the unique shape, pattern, and position of facial features
Can be based on still or video images
Face biometrics can be applied covertly, and without person’s cooperation

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19
Q

2D Facial Recognition

A

A template can be created from a standard webcam
There is no contact with a sensor
Can be done from a far distance
Highly affected by lighting, position, eyeglasses, facial expressions
Relies heavily on controlled environment resulting in a high failure rate
Technologies for face recognition
Eigen face approach: Face appearance
Feature geometry: feature-based method
Neural network

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20
Q

3D Facial Recognition

A

Uses real-time capture of three-dimensional images of a subject’s face
The uniqueness of the person’s cranio-structure (skull curvature,..) is extracted and stored as a biometric template
Not affected by lighting, background colors, facial hair or makeup,
Uses structured light in near-infrared range where a projector shoots an invisible structured light pattern onto the face, and a video camera records the pattern distorted by the face’s surface geometry
A 3D mesh of the face is created by means of triangulation

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21
Q

Iris Recognition

A

Measures the features associated with the random texture of the colored part of the eye
Based in visible features i.e.
rings, furrows, freckles, and the corona
Requires cooperation from the user
Weakness:
fear and discomfort, proprietary acquisition devices.

Highly accurate
Very stable over-lifetime
It works perfectly even with glasses and contacts
It can be affected though by some diseases such as cataracts.

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22
Q

Iriscode

A

Uses near infrared sensors at a distance of 6 inch to 2 ft
You can measure up to 255 unique features. Features and their locations are used to form the iriscode, which is the digital template
Iris picture can be captured using a normal CCD camera with a resolution of 512 dpi or higher
Different Iriscodes care compared using Exclusive OR

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23
Q

Retina Scan

A

Based on the vascular structure at the back of the eye:
The pattern of blood vessels that emanate from the optic nerve and disperse throughout the retina depends on individuals and never change
An infrared light source is shone through the eye’s pupil to luminate the retina
Extremely accurate and secure
No two retinas are the same even for identical twins

It is considered intrusive, it can reveal some medical conditions, such as hypertension
Requires the user to remove eyeglasses
Long capture time, with 5-15 sec.

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24
Q

Most Significant Test Measures of Biometrics Systems

A

False Matching Rate (FMR)
False Non-Match Rate (FNMR)
Failure to Enroll (FTE)
Equal-Error-Rate (EER)

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25
False Matching Rate (FMR)
Also referred to as False Acceptance Rate (FAR) The ratio between numbers truly non-matching samples, which are matched by the system and total numbers of test. It is the probability that a user making a false claim about her identity will be verified as that false identity It usually tell you the strength of the matching algorithm
26
False Non-Match Rate (FNMR)
Also referred to as False Rejection Rate (FRR) The ratio between numbers truly matching samples, which are not matched by the system and total numbers of test. It is the probability that a user making a true claim about her identity will be rejected as herself. It usually tell you the accuracy and robustness of the matching algorithm
27
Failure to Enroll (FTE)
It is the probability that a user attempting to biometrically enroll will be unable to. Vendors usually use the Rule of Three. It usually tell you the coverage for the population that the biometric system has.
28
Equal-Error-Rate (EER)
The point on the error rate diagrams where the false match and false non-match are equal Can be computed from the crossover point of FRR/FAR or using the Receiver Operating Characteristics (ROC).
29
What is Convergence?
Formal Cooperation between (at least) two separate security functions Streamlined Provisioning/de-Provisioning Shared Authentication Credentials Common Security Policies
30
Where is Convergence?
Commercial Proprietary Enterprise Systems Federal FIPS 201/PIV Standards driven Open interoperable system
31
Physical Access Control
Support multi-factor authentication in many combinations Fingerprint biometrics Face biometrics Proximity cards Smart cards Personal Identification Numbers (PIN)
32
Logical Access Control
Multi-factor Authentication Solution that uses a wide range of strong authentication methods. Enterprise Network Logon for desktop and network security. Enterprise-level Single Sign On for Windows and Web applications. Managed by a robust and extensible Role- Based Access Control Policy Engine.
33
Common Credentials /Policies) use?
Both physical and logical control
34
Benefits – Converged System
Common policies across physical and logical access Role-based Authorization Harmonized security privileges Centralized Enrollment Processes Similar models for Commercial and Government systems A range of Authentication Factors can be coordinated Authentication factors can be “cascaded” Events can be coordinated
35
Smart Cards
Card with the capability to store and/or process information for a particular application Can store financial, personal, and specialized information Types of smart cards Memory: only memory card; more storage than the magnetic strip Microprocessor: Memory, processor, and co-processor to support cryptography
36
Driving Factors for the Smart Cards
Declining cost in the price of smart cards From $15 in the 1980’s to couple of dollars in 2000, to sub-dollars now Fears that magnetic strip cards can’t provide the necessary security against fraud and security breaches.
37
Forms of Smart Cards
Smart cards come in two forms Contact Contact-less. May contain its own battery, Most of the times, the power is supplied by an inductive loop
38
Contact Smart cards
Identified by its gold connector plate ISO Standard (7816-2) defined eight contacts, Though only 6 are actually used: 8 metallic pads on the surface: Vcc: supply voltage - generally, 5 volts. GND: ground reference RST: Reset is the signal line that is used to initiate the state of card- Reset the microprocessor Clock: used drive the logic of the IC (Clock Signal) Vpp: used for the high voltage signal that is necessary to program the EPROM memory. Serial input/output (SIO) connector: used to receive commands and interchanges data with the outside world. 2 RFU: reserved for future use.
39
Smart Card Hardware
Microprocessor unit (MPU) 32-bit RISC I/O Control: manage the flow of data in/out of the card RAM: for temporary storage ROM for Chip OS (COS) or Mask EEPROM: Application memory (Electrically erasable programmable ROM) For permanent application data storage
40
Chip OS (COS)
A Chip OS is required to: Manage data in/out of the card Manage of files Access the data and function Management of card security Maintain reliability, interrupt, data consistency, error recovery A COS can be General purpose COS for all applications Dedicated COS for specific applications No standard COS
41
Security Features of Smart Card
Card level protection by several passwords Card get reset in case of hardware attack File level security Secret password based A second password based External authentication Encrypted Mutual authentication
42
Mandatory – PIV Card Storage - Interoperability
Two Index Fingers Templates generated from segmented 10-print enrollment images Stored as ANSI/INCITS 378 templates PIV Card fingerprint templates Interoperable PIV Card fingerprint templates can only be read through the contact interface following entry of a PIN
43
PIV Card Interoperability
PIV Card used for Logical and Physical Access Logical Access primarily based on PKI PIN required for access to private key and other data Physical Access systems typically not configured for PKI Physical Access systems typically based on contactless readers for throughput and durability Questions/Concerns How to achieve interoperability across both logical and physical access whilst meeting the demands of both environments?
44
PAC Biometric Readers – contactless interface
Interoperable PIV Card fingerprint templates can only be read through the contact interface following entry of a PIN However, the card holder unique ID (CHUID) can be read from the contactless interface and without a PIN Also, Agency-specific data (biometric template) can be written to PIV Card and accessed via contactless interface Can appropriate biometric PAC Scenarios for FIPS 201 be established using the CHUID and biometric template?
45
PAC Biometric Readers – Operational biometric templates
SP 800-76, Sec. 1.2 states: “...for both logical and physical access applications, and for applications using biometric data stored either on or off the PIV Card, this document neither requires nor precludes the use of: The PIV Card fingerprint templates; Specific authentication paradigms such as match-on-card; Data from other biometric modalities (e.g., hand geometry, iris, etc.); Data formatted according to other standards; Data whose format is proprietary or otherwise undisclosed.”
46
PAC Biometric Readers – PIN
Biometric Industry Association Viewpoint: PIN entry is not necessary for Minutiae templates Previous privacy issues related to full fingerprint images Biometric Templates stored on PIV Card are digitally signed A live version of the biometric sample is required for verification Mutual Authentication between card and reader can provide template privacy Consider 2-factor Authentication Use Cases with Contactless Access to PIV Card and Biometrics
47
Summary scenarios
Read off slides
48
Authentication can be Based on Different Concepts:
Knowledge Possession Biometrics Any combination of the three
49
Biometrics Based Authentication
Biometrics = bio (life) + metrics (to measure) Deals with automated methods of verifying or recognizing living persons based on their: Biological characteristics (e.g., face, fingerprint, iris, hand geometry, retina) Behavioral characteristic (e.g., signature, gait) Combined (e.g., Voice) No human involved in the authentication process Should be done in real-time
50
Facial Recognition
51
Most Significant Test Measures of Biometrics Systems
False Matching Rate (FMR) False Non-Match Rate (FNMR) Failure to Enroll (FTE) Equal-Error-Rate (EER)
52
Fingerprints how it works
Based on the ridges of the fingers Very mature technology especially in forensic applications Can use live-scan or inked impression
53
Fingerprints consideration
Fingerprints don’t change over time Things to consider: Small population might not be able to use it because of cuts, scars, occupational requirement. Requires a contact with a sensor Highly associated with law enforcement Attacks on Fingerprints Finger decapitation “Gummy” fingers Defenses Measure physical properties of a live finger (pulse, oxygen level).
54
Friction Skin Anatomy
Minute ridges with furrows between them are present on the inside surface of hands and feet of human beings. Such a structure, called friction skin, allows for: Good grip Good sense of touch Exudation of perspiration The structure and function of friction skin is different from other skin that covers our fingertips: Not covered by hair Does not contain oil glands It contains a high concentration of nerve endings and sweat glands A lack of pigmentation
55
Permanence and Uniqueness of Fingerprints
Fingerprints are permanent marks on the skin. They are formed at the fetal stage and stay the same throughout lifetime. Fingerprints of an individual are “unique” features of the individual; different person, even identical twins, have distinctive fingerprints. Around 4% of the human population though might be born without fingerprints or their fingerprints might have deteriorated
56
Applications of FP: Government
Criminal records Finger prints for diplomats and military personnel National identity card E-voting
57
Applications of FP: Forensic
Link a person to the crime place Link person to previous records (history)
58
Applications of FP: Civil and Commercial Applications
Banking Welfare Smartcards Access Control Time and Attendance
59
Fingerprint Authentication System
Sensing Feature extraction Matching
60
Fingerprint Sensing
Taking an imprint of the fingertip On-line acquisition or off-line fingerprint acquisition using the ink-technique. Nowadays, live-scan is the most widely fingerprint acquisition technique used.
61
Off-Line Acquisition
Adv: possibility of producing rolled impression
62
Specifications for a Good Fingerprint
Considerations Resolution Area Dynamic range Image quality Signal to Noise
63
FP Scanning: Scanners
Sweep and touch systems
64
Live-Scan
3 Main categories: Optical sensors Solid-state sensors or silicon sensors Ultra-sound sensors. Additional Multispectral 3-D touchless
65
Feature Extraction
A fingerprint is produced when a fingertip is pressed against a smooth surface producing ridges (black in the picture) and valleys (white).
66
Levels of Fingerprint Features
Level 1: refers to macroscopic patterns formed by the flow of the ridges Level 2: refers to major ridge path deviations, also known as minutiae. Level 3: refers to intrinsic or innate ridge formations: the alignment and shape of each ridge unit, pore shape, and relative pore positions).
67
Level 1 Features–Singularities
Singularities are regions where ridges assumes distinctive shapes: – Loop, delta, whorl, core
68
FP Classification
Used as index for searching a large DB of fingerprints. FP can be broadly classified into: Left and right loop, whorl, Arch and tented Arch
69
Fingerprint Class Distribution
5% of the FP have Arch type 65% of the FP have Loop type 30% of the FP have Whorl type
70
Level 2: Minutiae.
Minutia: refers to various ways that a ridge can be discontinued For each minutia, we keep: the x,y coordinates The angle of the tangent line to the ridge with the x-axix The FBI model considers only termination and bifurcation minutiae
71
Level 3: Sweat Pores
72
Steps for Feature Extraction
Local Ridge Orientation Local Ridge Frequency Singularity Detection Segmentation Fingerprint Enhancement Binarization Thinning Feature Extraction
73
Fingerprints: Strength and advantages
Fingerprints are unique Fingerprints are not time-variant A very mature and proven core technology It can provide a high level of accuracy It can be deployed in a range of environments Uses ergonomic and easy-to-use devices Numerous sources (ten fingers) available for collection
74
Fingerprints: Disadvantages or weaknesses
Associated with crime control/investigation Require user cooperation Cuts and scars will affect fingerprints Sensor interoperability Hygiene: Important to keep capture surface clean Most devices are unable to enroll some small percentage of users
75
What can we learn from a Speech?
Message, Language, Speech disorders/pathologies, Emotional state, and Speaker identity Voice Biometric: Automated use of voice as the biometric trait to recognize speakers
76
‘Speaker Identity’ in the Speech Signal
Physiological factors: Vocal tract characteristics, articulatory organs: dimension of vocal cavities, length of vocal tract and folds, etc. Linguistic Habits: phonological, prosodic (emotional state of the speaker, sarcasm, focus,…), linguistic and semantic habits (influenced by geographic, family, socio-cultural and professional factors)
77
Multiple Level of Speaker Individuality in a Speech
Idiolectal: how a speaker use a specific linguistic system Considered as a linguistic pattern unique among speakers Determining factors include: Family, level of education, sociological, region,… Phonotactics: describes the use by each speaker of the phonemes units and possible realizations available. Not all languages have same phonemes Key in foreign language training
78
Advantages of Speaker Verification
Automatic and natural (unlike fingerprinting), Low cost of input device: Can use standard microphone or telephone set Low cost of processing using DSP technology, Telemetric - Most suited modality over the telephone User friendly - non-invasive, lacks the negative perceptions associated with other biometrics such as fingerprint Can collect samples from uncooperative subjects. Can be combined with challenge/response techniques
79
Disadvantages of Speaker Verification
Affected by pathological changes in physical characteristics (cold) Less unique than fingerprints, iris,, retina,…DNA. more susceptible to replay attacks than other biometrics. Its accuracy is challenged by low-quality capture devices, ambient noise, channel, distortion and so on. Temporal drift The large size of the template limits the number of potential applications.
80
EXAMPLE QUESTIONS
81
A natural recognition capability for a human being is known as?
AUTHENTICATION
82
T or F Verification confirms who am I?
FALSE
83
Authentication can be based off the following concepts:
Possesion Biometrics Knowledge
84
What is not a problem for posssesiop based authetication compared to knowledge based?
No need to remember the password
85
A major drawback of knowledge based?
Can be guessed by imposters
86
Which of these options is not a biological characteristic: Gait. hand geometry, face, fingerprint
Gait
87
T/F: In biometric authenttication no human is involved in the authetication process
True
88
What is meant by Non-repudent in biometric system authetication
Access is linked to a person
89
What is a predesesor to modern biometric systems/tech?
Antropometry
90
Which of the following is not a criterion for biometric features: )Accesibility. Permanence. Circumvention, Universality)
Universality
91
List 5 basic functions of biometric systems sequentially:
Capture, Process, Enrollment. Identification, Verification
92
Verification is considered 1 to many T/F?
False
93
Identification " Am i who I claim to be?" T/F
False
94
What is convergance in relation to biometric tech in support of identification and access control?
Formal cooperation between atleast 2 seperate security functions
95
A key selling point of integration of biometric tech in access control/time and attendence measures is?
Clear return on investment
96
Convergance allows for?
Streamlined provisioning. Shared credentials, common security policies
97
Contact smart card ISO standard (7816-2) defined how many contracts?
8
98
Contact smart card ISO standard (7816-2) , how many are actually being used?
6
99
Chip OS is required for smart card tech to ensure?
Data access and functionality
100
In implementing a biomtric solution when do u consider a smart card?
Security and confidentiality of the record is important
101
What is not an advantage of smart card tech?
Scalability of the solution
102
Smart cards under development can do all the processing on the card?TF
True

Uni (2 decks)

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