Fingerprint Authentication

1
Fingerprint Authentication

• Dr. Lynne Coventry

2
What is Biometrics?

• Biometrics can be defined as the use of
  anatomical, physiological or behavioural
  characteristics to recognise an individual or
  verify the claimed identity of an individual.
• Techniques use characteristics of
• Fingerprint ? Eyes
• Face ? Hands
• Voice ? Signature
• Walk ? Typing

3
Why use Biometrics?

• Biometrics techniques are used to confirm that a
  person is actually present, rather than just
  their token or identifier.
• A name, password, key, card, PIN, number,
  specific knowledge (e.g. mothers maiden name)
  does not confirm the presence of the legitimate
  owner they can only confirm that the correct
  token or knowledge is being used and assume that
  the user is genuine.

4
Considerations for ATM use

• What needs to be considered before deploying a
  customer-facing biometrics solution at an ATM?
• Users
• Environment
• System

5
User Considerations

• User Base (Number of users)
• Outliers (People who cannot use system (FTE)
• Enrolment Training requirements
• Accessibility issues
• Usability (speed, errors, attitude)
• Public Acceptance
• Perceived Security
• Privacy
• Speed
• Hygiene

6
Why Fingerprint?

• Fingerprint is considered one of the most
  effective techniques but there can be problems
  with dirt, dry or worn prints and also with very
  fine prints.
• Fingerprint sensors are small and low cost (typ.
  10 for sensor) and easy to integrate/replace.
• They can be deliberately damaged.
• Template sizes tend to be small (lt1k) so easy to
  move and store.
• Can match 1-to-1 in few (typically 2) seconds.
• Public awareness and exposure.
• Requires positive user participation. Contact is
  necessary. Finger placement is important.

7
Why Radio Frequency?

• The system tested has a unique, patented image
  capture device based on active RF signal
  detection
• It has security, dirt resistance, spoof
  resistance built in to the chip
• Comparing the main variable criteria below to the
  other main fingerprint image capture techniques
  it is clearly the best system

8
Dynamic Optimization Dry Finger

• This example took 4 frames
• Executed in about ½ second on a PC

4
Adjust A/D references
In Slow Motion . . .
3
Increase amplifier gain
2
Increase drive signal
1
9
Testing Biometrics

• Method affects performance achieved
• Lab conditions with small homogenous set of good
  trained young cooperative users
• Real world has great variabilty, uninformed and
  even hostile users
• Performance Measures
• FAR
• FRR
• FTE
• FTA

10
Fingerprint Proof of Principle

• Maximise usability and acceptance of fingerprint
  at the ATM
• Running usability trials and iteratively
  designing interaction
• inhouse intuitive behaviour, sensor size
• inhouse iterative design and evaluation of
  leadthrough
• full consumer trial
• Rewriting application for self service
  environment
• Investigating integration issues with ATM software

11
Study 1 Size and intuition

• 76 users (enrol 10 V)
• Enrolment results.
• Only 2 people failed to enrol
• 14 people were asked by the system to repeat the
  enrolment
• 10 validation errors (FR)
• High individual variability.
• Quality and core placement issues
• Small sensor is acceptable but requires software
  refinement.
• Use core information to help the user
• Good enrolment is paramount to successful
  validation.
• Need for education about fingerprint core
• What was required as well as how to do it

12
Study 2 Improving training and leadthrough

• Iterative development
• moving red line
• Taught to locate core
• Teaching standardised
• software leadthrough to use the core to tell the
  user how to move
• Results
• removed all failure to enrol
• more consistent performance
• Only 2.5 false rejects

13
Study 3 Consumer Trial

• Use representative general public group across
  age, gender and occupation
• 168 Participants
• Random convenience sample, recruited in Edinburgh
• 60 under 50 and 40 over 50
• 52 male 48 female
• Identify attitude/acceptance
• Identify remaining usability issues
• Improved enrolment
• Improved leadthrough (target versus image)

14
Selected findings

• Still no real usage of biometrics
• 97 never used biometrics before
• Insecure behaviour
• 24 have their PIN written down
• 26 share their PIN and card
• Now percieved need
• Security and Convenience both an advantage and a
  disadvantage for fingerprint and PIN
• New technology concerns remain (50)
• Privacy concerns remain for minority (20)
• General willingness to accept (60 -gt 70)

15
(No Transcript)
16
Performance

• 13 failure to enrol rate
• Problems getting good enrolment images
• image quality
• all from over 60s mainly female
• 10 false reject rate
• poor templates
• inconsistent placement of finger
• placing more restriction on placement or image
  quality will increase failure to acquire
• Still to complete more detailed analysis of
  performance

17
Usability issues remain

• People do not understand the concept of the
  fingerprint core
• A central core image is essential
• People tend to place their finger too low on the
  sensor
• Pre-training is crucial to successful enrolment
• Good enrolments form the basis of consistent
  validation
• Still need human intervention in the enrolment
  process

18
Future Trials

• Explanation of technology for participants
• Explain difference between verification and
  identification
• Trial new RF device
• same size, higher DPI
• Trial concerning problem group
• Elderly above 60
• Improvement in leadthrough
• combine target and image leadthrough

19
Biometrics evaluations conclusions
Actual uptake
Use
Real acceptance with customers
Pluralistic approach
Potential acceptance with representative user
population
Fingerprint, iris, PIN
Pilot
Speech, facial, fingerprint, iris, PIN
Lab tests
usability
Functional Prototype tests
Speech, facial, fingerprint, finger swipe, iris,
PIN
Worries, problems, fears
Speech, hand geometry, finger geometry, facial,
fingerprint, iris, PIN
Focus Groups
20
Conclusions

• Biometrics can increase security and improve risk
  management
• For niche applications, biometrics makes good
  business sense, are popular and appear to be
  successful
• Successful biometrics systems are dependent on
  successful enrolment
• For the general ATM user population usability
  issues will impact security.