Basics of Biometrics

1. D O N C A E I R O
BIOMETRICS

2. INTRODUCTION
• Measuring and statistically analyzing biological data.
• Physiological and / or behavioral characteristics.
• Unique to each individual.
• The term “Biometrics” literally means “life measurement”.
• Main application is- security.

3. BIOMETRIC CHARACTERISTICS
• Universal
• Invariance of Properties
• Measurability
• Singularity
• Acceptance
• Reducibility
• Reliability and tamper-resistance

4. OPERATION
• A sensor takes an observation.
• This observation gives us a Biometric Signature of the individual.
• A computer algorithm normalizes the biometric signature.
• A matcher compares the normalized signature with the set (or sub-set) of
normalized signatures on the system's database

5. COMPONENTS OF BIOMETRIC SYSTEMS
• Sensor Module. Eg- Retina scanner/Fingerprint Sensor
• Feature extraction modules
• Matching modules
• Decision-making modules

6. ENROLLMENT, VERIFICATION AND IDENTIFICATION
• Stores some biometric reference information about the person in a database.
• As features of the particular biometrics (template)
• Verification- one to one comparison (present biometric with template stored.
• Identification- One to many in a database.

7. SENSORS
• Optical Sensors
– Optic reflexive
– Optic Transmissive
– Fiber Optic Plate
• • Capacitative/semiconductor Sensors
– Static Capacitative I, II
– Dynamic Capacitative
• Ultrasound sensors

8. OPTICAL SENSOR

9. TOUCHLESS SENSORS- SURROUND PRINT

10. CLASSIFICATION OF BIOMETRIC
SYSTEMS

11. PHYSIOLOGICAL
• analyze data such as facial features, eye structure (retina or iris), finger
parameters (papillary lines, relief, length of joints, etc.), palm (print or
topography), hand shape, vein pattern on the wrist, and heat pattern.
• for example, access control to smartphones and laptops
• Face
• Fingerprint
• Veins geometry
• Retina
• Iris recognition

12. PROS
• An identifier is inseparable from a person; it cannot be forgotten, lost, or
passed on. Having checked the identifier, we can say with a high degree of
certainty that this particular person was identified.
• It is quite difficult to recreate (fake) an identifier.
• The process of biometric identification is fast and completely performed by
computers.
• Identification can be carried out transparently (invisibly) for a person.

13. CONS
• The need for certain environmental conditions for biometric identification.
• Situations can arise where biometric identifiers are damaged or unavailable
for reading.
• For many biometric identification systems, biometric scanners are quite
expensive.
• It is necessary to comply with the requirements of regulators for the
protection of personal biometric data.

14. BEHAVIORAL BIOMETRICS
• involves the collection of a wide variety of data.
• physical and cognitive behaviour
• also called passive because users do not need to take any additional steps
when operating
• can also detect fraud early, even before the attacker's act (for example,
stealing from stores or making a purchase).
• Some Examples
• the speed with which they type on the keyboard
• the force of pressing the keys
• the angle at which they move their fingers across the screen.

15. PROS
• Individual user set of analyzed behavioral characteristics.
• No custom script change is required to perform identification: seamless
integration method.
• Improves recognition accuracy in multifactor identification systems.

16. CONS
• Inaccuracies in identification may arise because the user's behavior is not
always constant since they can behave differently in various situations due to
fatigue, drunkenness, feeling unwell or trivial haste.
• Behavioral biometrics are not yet widely adopted.
• Requires lots of personal data to determine a user's standard behavior.

17. DNA MATCHING
• Category: Chemical
Industry Leaders: Innocence Project, 23andMe, Family Tree, Ancestry
Use-Cases: Forensic science, calculating family ties between people and
determining their predisposition to various diseases based on their DNA
samples
Security Level: Very High

18. PROS
• DNA is the only biometric technology that allows you to identify relatives
using an unidentified DNA sample
• Like fingerprints, DNA is one of the few biometric characteristics of a person
that criminals leave behind at a crime scene
• DNA testing is a relatively mature and dynamic technology that is widely used
and familiar to the public
• Rapid DNA identification devices make sequencing possible in just 90
minutes
• Many DNA analysis results can be easily stored in databases, allowing data
to be accumulated and quickly searched by automated means

19. CONS
• Low representation in the biometric market
• Identical twins will share the same DNA
• Accuracy Level: Very High

20. FACIAL RECOGNITION
• Category: Visual & Spatial
Industry Leaders:
20 major vendors, namely, NEC (Japan), Aware (US), Gemalto
(Netherlands), Ayonix (Japan), Idemia (France), Cognitec (Germany), nVviso
SA (Switzerland), Daon (US), Stereovision Imaging (US), Techno Brain
(Kenya), Neurotechnology (Lithuania), Innovatrics (Slovakia), id3
Technologies (France), Herta Security (Spain), Animetrics (US), Megvii
{Face++} (China), FaceFirst (US), Sightcorp (Netherlands), FacePhi (Spain),
and SmilePass (UK).
Use-Cases: Controlling access to objects or systems, identification for video
management systems, determining the profile of the customer, identification
in the banking sector, time attendance systems, biometric authentication,
payment for services
Security Level: High

21. PROS
• High accuracy of recognition
• Wide range of parameters (the algorithm is not affected by age differences,
lighting, head position, etc.)
• Performance (result in a split second in a multi-billion database)
• Scalable architecture (nationwide search)
• Mobility (results in the field)
• Accuracy Level: High

22. CONS
• Data storage difficulties. Identification efficiency develops with the number of
identified faces in available databases, which is still very far away from world-
wide or even country-wide numbers
• The efficiency can decrease due to the low quality of camera resolution and
lighting issues
• Identify forgery. It is still very hard to trick the system into believing that you
are someone else, but there are relatively easy methods to hide your identity,
like using special makeup

23. FINGERPRINT RECOGNITION
• Category: Visual & Spatial
Industry Leaders: NEC Corporation, Idemia, ID R&D, Apple Inc, Samsung,
IBM
Use-Cases: Device authentication (smartphone, laptop, flash drives, etc.),
identification of criminals, identification in the banking sector
Security Level: High

24. • Pros:
• Easy to use
• Convenience and reliability
• Low cost of devices that scan a fingerprint image
• Cons:
• Inability to read the print with some scanners with excessively dry skin
• Violation of the papillary pattern by small scratches, cuts, chemical reagents
can affect recognition
• Accuracy Level: High

25. PALM BIOMETRICS

26. PALM BIOMETRICS
• Category: Visual & Spatial
Industry Leaders: NEC Corporation, MegaMatcher, ZKTeco, DERMALOG
Use-Cases: Device authentication (smartphone, laptop, flash drives, etc.),
identification of criminals, identification in the banking sector
Security Level: High

27. • Pros:
• It is possible to capture more distinctive features than fingerprints
• Fast scanning
• Safe for users
• May be contactless
• Cons:
• Palm print scanners tend to be bulkier and more expensive than fingerprint
scanners
• Accuracy Level: High

28. IRIS BIOMETRICS

29. • Category: Visual
Industry Leaders: EyeLock, Apple, Samsung, Fujitsu Ltd
Use-Cases: Integration in the access control system, identifying persons in
special areas (airports, border control areas, passport offices)
Security Level: High

30. • Pros:
• Fast scanning
• Contactless
• Safe for users
• Recognition does not depend on glasses or contact
lenses
• Impossibility of counterfeiting
• Cons:
• Minor eye injuries can affect recognition
• Deterioration in identification after taking alcohol or LSD
• High integration cost
• Accuracy Level: High

31. RETINAL SCAN
• Category: Visual & Spatial
Industry Leaders: EyeLock, CMITech, BioEnable, FotoNation, IDEMIA
Use-Cases: Identification in the banking sector, controlling access to objects
or systems
Security Level: Very High

32. • Pros:
• Almost impossible to counterfeit
• High accuracy
• Fast recognition time
• Cons:
• Negative impact on eye disease (cataract or glaucoma)
• Low level of public acceptance
• High false rejection rate
• Accuracy Level: Very High

33. KEYSTROKE DYNAMICS
• Category: Behavioral
Industry Leaders: TypingDNA, ID Control, BehavioSec
Use-Cases: Device user identification, part of multifactor authentication,
used for observation
Security Level: High

34. • Pros:
• No special equipment is required for this method
• Fast and secure
• Hard to copy by observation
• Cons:
• Typing rhythm can change because of fatigue, illness, the effects of drugs or
alcohol, keyboard changes, etc.
• Can't identify the same person using different keyboard layouts
• Accuracy Level: High

35. SIGNATURE BIOMETRICS
• Category: Behavioral
Industry Leaders: Aerial, Redrock Biometrics, Sense, University of Oxford,
Mobbeel
Use-Cases: Document verification and authorization, identification in the
banking sector
Security Level: High

36. • Pros:
• Almost impossible to counterfeit
• Widespread in business practice
• Fast and secure
• Convenience of integration
• Cons:
• High recognition error rate until user get used to signing pad
• Hand injuries can affect recognition accuracy
• Accuracy Level: Medium

37. SPEAKER RECOGNITION
• Category: Behavioral, Auditory
Industry Leaders: Apple Inc, Microsoft, Google LLC
Use-Cases: Telephone and internet transactions, sound signatures for digital
documents, online education systems, emergency services
Security Level: Low

38. • Pros:
• Convenience of integration
• Fast recognition time
• Contactless scanning
• Cons:
• Sensitivity to microphone quality and noise
• Risk of counterfeit
• Accuracy Level: Low

39. GAIT RECOGNITION
• Category: Behavioral
Industry Leaders: SFootBD, Watrix, Cometa Srl
Use-Cases: In the medical and forensic sectors
Security Level: Low

40. • Pros:
• Contactless scanning
• Possibility to cover a large area
• Fast recognition time
• Technology is developing rapidly
• Cons:
• Not so reliable as other biometric methods
• Clothes and shoes can affect recognition accuracy
• Accuracy Level: Low

41. CONCLUSION
• Uses and applications
• Areas of concern
• Advantages- increase security, eliminate conventional methods of access.
• Disadvantages- wrt to different types of biometrics and their shortcomings.

42. MULTIMODAL BIOMETRICS

43. INTRODUCTION
• accepting information from two or more biometric inputs.
• unimodal systems must deal with various challenges such
as
• lack of secrecy
• non-universality of samples
• extent of user’s comfort and freedom while dealing with the
system
• spoofing attacks on stored data

44. WHY MULTIMODAL BIOMETRICS IS REQUIRED?
• Availability of multiple traits makes the multimodal system more reliable.
• A multimodal biometric system increases security and secrecy of user data.
• A multimodal biometric system conducts fusion strategies to combine
decisions from each subsystem and then comes up with a conclusion. This
makes a multimodal system more accurate.
• If any of the identifiers fail to work for known or unknown reasons, the system
still can provide security by employing the other identifier.
• Multimodal systems can provide knowledge about “liveliness” of the sample
being entered by applying liveliness detection techniques. This makes them
capable to detect and handle spoofing.

45. WORKING OF MULTIMODAL BIOMETRIC SYSTEM
• Multimodal biometric system has all the conventional
modules a unimodal system has −
• Capturing module
• Feature extraction module
• Comparison module
• Decision making module

46. WORKING OF MULTIMODAL BIOMETRIC SYSTEM
• In addition, it has a fusion technique to integrate the
information from two different authentication systems. The
fusion can be done at any of the following levels −
• During feature extraction.
• During comparison of live samples with stored biometric
templates.
• During decision making.

47. FUSION SCENARIOS IN MULTIMODAL BIOMETRIC
SYSTEM
• Single biometric trait, multiple sensors.
• Single biometric trait, multiple classifiers (say, minutiae-based
matcher and texture-based matcher)
• Single biometric trait, multiple units (say, multiple fingers).
• Multiple biometric traits of an individual (say, iris, fingerprint, etc.).

48. DESIGN ISSUES WITH MULTIMODAL BIOMETRIC
SYSTEMS
• Level of security you need to bring in.
• The number of users who will use the system.
• Types of biometric traits you need to acquire.
• The number of biometric traits from the users.
• The level at which multiple biometric traits need integration.
• The technique to be adopted to integrate the information.
• The trade-off between development cost versus system
performance.

49. EXPERIMENT RESULTS

50. CONCLUSION
• Multimodal biometric systems provide better
recognition performance.
• Different users tend to adopt differently to individual
biometric indicators. These weights can be learnt
over time by examining the stored template of the
user.

51. KEY BIOMETRIC PROCESSES

52. Ⅱ. BIOMETRIC SYSTEM
52
Basic Structure of Biometric

53. 53
BIOMETRIC SYSTEM
• A Biometric System Is Designed Using The Following Four Main
Modules.
1) Sensor Module
(Encapsulating a Quality Checking Module)
2) Feature Module
3) Matcher Module
(Encapsulating a Decision Making Module)
4) System Database Module

54. 54
BIOMETRIC SYSTEM (CONT..)
A sample flow chart:
Feature
Extractor
Sensor
Qualify
checker
System
Database
True / False
Matcher
Decision
Maker
template
The templates in the system database
may be updated over time.

55. 55
BIOMETRIC SYSTEM (CONT..)
• A biometric system may operate either in verification mode or identification
mode.
A. Verification mode:
“Does this biometric data belong to Bob? ”
B. Identification mode:
“Whose biometric data is this? ”
• “Recognition” is the generic term of verification and identification.

56. 56
BIOMETRIC SYSTEM (CONT..)
System
Database
Login
Interface
Get Name & Snapshot
Quality
Checker
Check Quality
Feature
Extractor
Enrollment
Template

57. 57
BIOMETRIC SYSTEM (CONT..)
System
Database
True / False
Login
Interface
Get Name & Snapshot
One template
Feature
Extractor
Extract Features
Matcher
One match
Verification
Claimed identity

58. VERIFICATION
• The person claims to be ‘John’, system must match and compare his/hers
biometrics with John’s stored Biometrics.
• If they match, then user is ‘verified’ or authenticated that he is indeed ‘John’ –
Access control application scenarios.
• Typically referred as 1:1 matching.

59. VERIFICATION
• This is the one-to-one process of matching where live sample entered by the
candidate is compared with a previously stored template in the database.
• If both are matching with more than 70% agreeable similarity, then the
verification is successful.

60. 60
BIOMETRIC SYSTEM (CONT..)
System
Database
User’s identity or
“user unidentified”
Login
Interface
Get Name & Snapshot
N templates
Feature
Extractor
Extract Features
Matcher
N match
Identification

61. IDENTIFICATION
• Match a person’s biometrics against a database to figure out his identity by
finding the closest match.
• Commonly referred to as 1:N matching
• ‘Criminal Watch-list’ application scenarios

62. IDENTIFICATION
• This process tries to find out answer of question,
• “Are you the same who you are claiming to be?”, or,
• “Do I know you?”.
• This is one-to-many matching and comparison of a
person’s biometrics with the whole database

64. FALSE ACCEPTANCE RATE (FAR):
• It is the measure of possibility that a biometric system will incorrectly identify
an unauthorized user as a valid user.

65. FALSE REJECT RATE (FRR):
• It is the measure of possibility that the biometric system will incorrectly reject
an authorized user as an invalid user.

66. VIDEO
• https://www.youtube.com/watch?v=-NcnbYEdqBk&t=17s