This document discusses biometrics sensors and various biometric authentication methods. It describes conventional authentication using something you have, like a card, or something you know, like a password. Biometric authentication uses personal features like fingerprints. The document outlines different biometric technologies including fingerprint, face, iris, hand, and signature recognition. It discusses applications and results from tests that showed many biometric systems can be fooled, though methods and difficulty varied between systems. Overall, the document presents an overview of biometric sensors and technologies while noting security issues that manufacturers need to address to improve biometric authentication.

1. Biometrics Sensors
Submitted by:- Sukhdeep Singh Sidhu
Roll No. :- 115363
Branch:- CSE N2

2.  Authentication – the process of verifying that a
user requesting a network resource is who he,
she, or it claims to be, and vice versa.
 Conventional authentication methods
› „something that you have“ – key, magnetic card or
smartcard
› „something that you know“ – PIN or password
 Biometric authentication uses personal features
› „something that you are“

3. Contents
 Application domains for biometric products
 Biometric products
 Fingerprint recognition
 Face recognition
 Iris recognition
 Retinal recognition
 Hand geometry measurement
 Dynamic signature verification
 How good are biometric products today?
 Conclusions

4.  Access control
› to devices
 cellular phones
 logging into a computer, laptop, or PDA
 cars
 guns
› to local services
 debitting money from a cash dispenser
 logging in to computer
 accessing data on smartcard
› to remote services
 e-commerce
 e-business

5.  Physical access control
› to high security areas
› to public buildings or areas
 Time & attendance control
 Identification
› forensic person investigation
› social services applications, e.g. immigration or
prevention of welfare fraud
› personal documents, e.g. electronic drivers
license or ID card

6.  Sensors
› optical sensors
› ultrasound sensors
› chip-based sensors
› thermal sensors
 Integrated products
› for identification – AFIS systems
› for verification

7. Electro-optical sensor
[DELSY® CMOS sensor modul]
Optical fingerprint sensor
[Fingerprint Identification Unit
FIU-001/500 by Sony]
Capacitive sensor
[FingerTIP™ by Infineon]

8. Thermal sensor
[FingerChip™ by ATMEL
(was: Thomson CSF)]
E-Field Sensor
[FingerLoc™ by Authentec]

9. [BioMouse™ Plus by American Biometric Company]
Physical Access Control System
[BioGate Tower by Bergdata] [ID Mouse by Siemens]

10. Keyboard [G 81-12000
by Cherry]
System including
[TravelMate 740 by Compaq und Acer] fingerprint sensor,
smartcard reader and
display by DELSY

11. Face recognition system
[TrueFace Engine by Miros]
Face recognition system
[O n e -t o -O n e ™ b y B io m e t r ic Ac c e s s C o r p o r a t io n ]

12. S y s t e m f o r p a s s iv e ir is r e c o g n it io n b y S e n s a r
S y s t e m f o r a c t iv e ir is
r e c o g n it io n b y Ir is S c a n

13. Retinal recognition system [Icam 2001 by Eyedentify]

14. Hand geometry reader by Recognition Systems
Hand geometry reader for
two finger recognition by BioMet Partners

15. Electronic pen [LCI-SmartPen]

16. Digitising tablet by Digitising tablet [Hesy Signature Pad
Wacom Technologies by BS Biometric Systems GmbH]

17.  Combination of biometric technologies
› Fingerprint and face recognition
› Face recognition and lip movement
› Fingerprint recognition and dynamic signature
verification
 increase the level of security achieved by
the system
 enlarge the user base

18.  depends on the application
 reliability
 security
 performance
 cost
 user acceptance
 life detection
 users that are unsuitable
 size of sensor

19.  How can we find out, how good a biometric
product is?
› Empirical tests of the product
 In the past year, there were two
independent test series of biometric products
› in Japan
› in Germany

20. 1. Regular biometric sensor
using artificially generated
biometric data
3. Replay attack of
eavesdropped biometric
data
5. Manipulation of stored
biometric reference data

21.  Tsutomu Matsumoto, a Japanese
cryptographer working at Yokohama
National University
 11 state-of-the-art fingerprint sensors
 2 different processes to make gummy fingers
› from live finger
› from latent fingerprint
 Gummy fingers fooled fingerprint sensors 80%
of the time

22.  Computer magazine c’t
 11 biometric sensors
› 9 fingerprint sensors,
› 1 face recognition system, and
› 1 iris scanner
 Fingerprint sensors –
› reactivate latent fingerprints (optical and capacitive
sensors)
› apply latex finger (thermal sensor)
 Face recognition system –
› down- (up-) load biometric reference data from (to) hard
disk
› no or only weak life detection

23.  Iris recognition –
› picture of iris of enrolled person with cut-out
pupil, where a real pupil is displayed
 All tested biometric systems could be fooled,
but the effort differed considerably

24.  Biometric technology has great potential
 There are many biometric products around,
regarding the different biometric technologies
 Shortcomings of biometric systems due to
› manufacturers ignorance of security concerns
› lack of quality control
› standardisation problems
 Biometric technology is very promising
 Manufacturers have to take security concerns
serious