1. Biometrics: Identity Verification in a Networked World
Transparent Multimodal Biometric System for HD Multimedia Conference
Biometrics: Identity Verification in a Networked World
Name: Laith Abbadi, Abbas Javadtalab

2. Introduction
Identification in electronic networks (e-Identification) is a main topic in e-world (e-commerce and e-government) [1].
A biometric system recognizes a person based on physiological or behavioral characteristics of the person.
A multimodal biometric system is a system that combines two or more of the biometric characteristics.

3. Purpose
The purpose of the paper is to verify the identity of a person during a video conference using a transparent multimodal biometrics.
The paper will propose a multimodal biometric system using face and ear recognition and without the user’s interaction.

4. Security Proposed Framework
For practical use, the framework is aiming to satisfy a set of criteria include:
(i)Ease of deployment:
A system can be deployed with few additional requirements on current infrastructure and communication protocols;
(ii) Ease of use:
Users have no difficulties using the system;
(iii) Security:
A system should address the real security concerns in verifying a person in the system. The security may not be perfect, but should be good enough to be user-friendly and business-driven

5. Authentication Type Table 1: Classification of authentication type
Description
Example
Identifier Group
Type 1
Something you know
Password, PIN
Knowledge based
Type 2
Something you have
Token, OTP
Electronic tokens
Type 3
Something you are
Fingerprint, iris, face, ear
Biometric (Physiological)
Type 4
Something you do
Voice, Signature
Biometric (Behavioral)

6. Identifier Groups Knowledge Based Identifiers Electronic Tokens
Date of Birth
SIN Number
Names
Address
PIN Numbers (passwords)
Electronic Tokens
Digital tokens are the physical devices that contain digital information for verification purposes.
a. Smart Cards
b. One time Password Token
OTP Time based Token
OTP Event based Token
c. Radio frequency identifiers (RFID).

7. Identifier Groups Biometric Identifiers
Physiological Biometric Identifiers:
Fingerprint
Retina image
Iris
Face Recognition
Ear Recognition
Behavioral Biometric Identifiers:
Voice
Dynamic signature
Keystrokes dynamics
Note: Using behavioral identifiers alone is not a solid solution, but they work well if they used with other types of identifiers.

8. Biometric for Verification
Biometric System
Table 2: Biometric Features
Features
Biometric for Verification
Biometric for Identification
Fingerprint √
Iris
Face Recognition
Ear Recognition
Voice
Dynamic Signature
Keystrokes dynamics

9. E-identifiers
Table 3: Comparison of e-identifier groups
Source: [1]

10. Biometric identifiers
Table 4: Biometric Identifiers [2]
Ear
Note: For Ear, research was not finished by Nov 3, 2010

11. HD Multimedia Conference
High quality video Conferencing
Used for communicating between CEO’s and VIP’s
Video Quality:1920x1080
x264:
Open source implementation of H.264 standard
x264 offers faster encoding

12. Sample Results (CBR)
Original
1200 Kbit/s
100 Kbit/s
800 Kbit/s

13. Multimodal Biometric Recognition system
Face Templates
Face Matching
Face Extraction
Ear Templates
Fusion
Ear Matching
Ear Extraction
Decision

14. Conference solution

15. Conference solution

16. Future Work 1- Apply face detection Algorithm
2- Apply ear recognition Algorithm
3- Apply voice detection
a.    Oral style (such as spelling ‘aahhh’)
4- Mouth movement
5- Face Expression & Emotion (ex. laughing)
8- Ration (face with upper body)
9- Add-ons
a.    Hand shake (haptics)

17. Conclusion
Use of Multimodal Biometric system is more advantageous than using a mono-modal biometric system
Biometric features are unique to each person
It is feasible to have a transparent verification system using face and ear recognition

18. Thank You

19. References
[1] Biometric Technology Today (BTT), June (2008) Biometrics in the retail sector page 9-11
[2] Black Cathryn, (2008) Biometric Technology Today • January 2008page 5
[3] Clarke Roger (2007) Introduction to Information Security, February 2007
[4] Clarke, Roger (2008), ``EDI is but one element of electronic commerce'', Roger Clarke's EC Foundation Paper
[5] Clarke, Roger (2005) Dataveillance by Governments The Technique of Computer Matching Information Technology & People, Vol. 7 No. 2, 2005, pp
[6] Clarke, Roger (2009) Human Identification in Information Systems: Management Challenges and Public Policy Issues
[7] Cranor L, Cytron R. Sensus:a security-conscious electronic polling system for the Internet. Proceedings of the Hawaii International Conference on System Sciences; p. 561e70.
[8] Desmarais Norman, (2009) Body language, security and e-commerce Volume 18 . Number pp
[9] Granova Anna & Eloff JHP, (2004) Online banking and identity theft: who carries the risk? Computer Fraud and Security page 7-8
[10] Marshalla Angus M., Tompsett Brian, (2005) Identity theft in an online world Computer Law & Security Report (2008) 21, 128e137
[11] Monrose Fabian, Rubin Aviel D. (2009) Keystroke dynamics as a biometric for authentication. Future Generation Computer Systems 16 (2009)