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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. Introduction.

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Biometrics: Identity Verification in a Networked World

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  1. Transparent Multimodal Biometric System for HD Multimedia Conference Biometrics: Identity Verification in a Networked World Name: LaithAbbadi, 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 transparentmultimodal 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

  6. Identifier Groups • Knowledge Based Identifiers • 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 System Table 2: Biometric Features

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

  10. Biometric identifiers Table 4: Biometric Identifiers [2] 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 800 Kbit/s 100 Kbit/s

  13. Multimodal Biometric Recognition system

  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 http://www.anu.edu.au/people/Roger.Clarke/EC/Bled08.ht • [5] Clarke, Roger (2005) Dataveillance by Governments The Technique of Computer Matching Information Technology & People, Vol. 7 No. 2, 2005, pp. 46-85 • [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; 2009. p. 561e70. • [8] Desmarais Norman, (2009) Body language, security and e-commerce Volume 18 . Number 1 . 2009 . pp. 61-74 • [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) 351-359

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