A Study of the Channel Mismatch Problem in a Multimodal Face-Voice Biometric Access System FALLON SARATOVSKY, TODD EDWARDS, RICH KUITERS, HUGH ENG, AND.

Slides:



Advertisements
Similar presentations
Technical Issues Regarding Near Field Communication Group 16 Tyler Swofford Matthew Kotan.
Advertisements

Technology Presentation E-Learning, hardware and the cloud.
Department of Labor HSPD-12
15 Tactical Improvements to IT Security Virtual Keyboard, Two Factor Authentication, Active Confirmation and FAA Access to CPS Online Ganesh Reddy.
Digital Ethnography Of Fiji. Empowering people to portray their Culture Through Technology.
3d ..
3D-password A more secured authentication G.Suresh babu Roll no:08H71A05C2 Computer science & engineering Mic college of technology Guide:Mrs A.Jaya Lakshmi.
Introduction to Biometrics Dr. Pushkin Kachroo. New Field Face recognition from computer vision Speaker recognition from signal processing Finger prints.
GUIDE TO BIOMETRICS CHAPTER I & II September 7 th 2005 Presentation by Tamer Uz.
Biometrics Austen Hayes and Cody Powell. Overview  What is Biometrics?  Types of Biometric Recognition  Applications of Biometric Systems  Types of.
Scholars Tracking Archival Resources Ciaran Trace, Unmil P. Karadkar School of Information The University of Texas at Austin.
Biometrics: Voice Recognition
Biometrics: Ear Recognition
Deb Gearhart Trot University Student Authentication – What it Means for Us.
Clustering methods Course code: Pasi Fränti Speech & Image Processing Unit School of Computing University of Eastern Finland Joensuu,
Speaker Recognition By Afshan Hina.
CS 736 A methodology for Analyzing the Performance of Authentication Protocol by Laseinde Olaoluwa Peter Department of Computer Science West Virginia.
July 25, 2010 SensorKDD Activity Recognition Using Cell Phone Accelerometers Jennifer Kwapisz, Gary Weiss, Samuel Moore Department of Computer &
1 Luke Klein-Berndt Command, Control and Interoperability Science and Technology Directorate November 8, 2007 Interoperability Tools & Resources 9th Annual.
Douglas A. Reynolds, PhD Senior Member of Technical Staff
Biometric User Authentication on Mobile Devices through Gameplay REU fellow: Kirsten Giesbrecht 1, Faculty mentor: Dr. Jonathan Voris 2 Affiliation: 1.Centre.
Zhengyou Zhang Microsoft Research Digital Object Identifier: /MMUL Publication Year: 2012, Page(s): Professor: Yih-Ran Sheu Student.
Introduction to Biometrics Charles Tappert Seidenberg School of CSIS, Pace University.
Normalization Normalization is the process of simplifying the relationship between data elements in a record[12] Database normalization is the process.
BY CHEN YEAH TECK Image-Based Authentication for Mobile Phones: Performance and User Opinions Source: Slippery Brick (2006)
Study of Comparison of Digital Forensic Investigation Models.
» Jun 9, 2003 Speaker Verification Secure AND Efficient, Deployments in Finance and Banking Jonathan Moav Director of Marketing
Vehicle License Plate Detection Algorithm Based on Statistical Characteristics in HSI Color Model Instructor : Dr. K. R. Rao Presented by: Prasanna Venkatesh.
BIOMETRICS By: Lucas Clay and Tim Myers. WHAT IS IT?  Biometrics are a method of uniquely identifying a person based on physical or behavioral traits.
Customer Dr. Beigi, Recognition Tech., Inc Hugh Eng, DPS ‘16 Dr. Tappert, CSIS Vinnie Monaco, PhD’15 Smartphone/Laptop Security Acceptability/Ease-of-Use.
Time Collection with Mobile Devices Session Presented by JP Issock Quality Business Consulting.
At a glance…  Introduction  How Biometric Systems Work ?  Popular Biometric Methodologies  Multibiometrics  Applications  Benefits  Demerits 
Abstract We present two Model Driven Engineering (MDE) tools, namely the Eclipse Modeling Framework (EMF) and Umple. We identify the structure and characteristic.
Signature with Text-Dependent and Text-Independent Speech for Robust Identity Verification B. Ly-Van*, R. Blouet**, S. Renouard** S. Garcia-Salicetti*,
Signature with Text-Dependent and Text-Independent Speech for Robust Identity Verification B. Ly-Van*, R. Blouet**, S. Renouard** S. Garcia-Salicetti*,
Security PS Evaluating Password Alternatives Bruce K. Marshall, CISSP, IAM Senior Security Consultant
Biometrics Stephen Schmidt Brian Miller Devin Reid.
WG1. Availability and evaluation of monitoring data Action FP0903.
Online Kinect Handwritten Digit Recognition Based on Dynamic Time Warping and Support Vector Machine Journal of Information & Computational Science, 2015.
Speaker Verification System in a Security Application HŪDATBrian Bash Thomas Jonell Dustin Williams Advisor Dr. Les Thede.
Keystroke Authentication It’s All in How You Type John C. Checco BiometriTech 2003 bioChec™
The Secure, Automated Home Project Team: Alec Kulbacki Project Advisor: W. Thomas Miller.
Information Security Audit Tool Presented by Bandar Almarashi Supervisor by Dr. Neville Williams.
The WG Workgroup on Child Functioning and Disability Elena De Palma *, Roberta Crialesi *, Mitchell Loeb** Washington Group on Disability Statistics *Italian.
Digital Libraries1 David Rashty. Digital Libraries2 “A library is an arsenal of liberty” Anonymous.
L. F. Coppenrath & Associates PASSWORD BIOPASSWORD ® Biometric Keystroke Dynamics Technology Overview.
Biometric Devices Biometric devices use secure identification and authentication in order for someone to use the device. These devices use automated.
Introduction to Biometrics Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #6 Guest Lecture + Some Topics in Biometrics September 12,
LEARNING AREA 1 : INFORMATION AND COMMUNICATION TECHNOLOGY PRIVACY AUTHENTICATION VERIFICATION.
BOPS – Biometric Open Protocol Standard Emilio J. Sanchez-Sierra.
By Kyle Bickel. Road Map Biometric Authentication Biometric Factors User Authentication Factors Biometric Techniques Conclusion.
Moving to BYOD Gary Audin 1.
Web - Mail – Sound Sensors Market Forecast ( )
An Introduction to Biometrics
3D Password.
By: Brad Brosig.  Introduction  Types of Biometric Security  The Installation Process  Biometric Authentication Errors  The Necessity of Mobile Device.
Study on Deep Learning in Speaker Recognition Lantian Li CSLT / RIIT Tsinghua University May 26, 2016.
TECHNOLOGY IN ACTION. Chapter 8 Digital Devices and Media: Managing a Digital Lifestyle.
COMPSCI 720 Security for Smart-devices Tracking Mobile Web Users Through Motion Sensors: Attacks and Defenses [1] Harry Jackson hjac660 [1] Das, Anupam,
Biometrics Reg: AMP/HNDIT/F/F/E/2013/067.
Biometrics Authentication
Multifactor Authentication & First Time Login
Follow My Voice: The Future of PHR Authentication
Proven Track Record Enhancing the User Experience just used your new facial recognition software on my iPhone.
Seminar Presentation on Biometrics
Biometric technology.
A SEMINAR REPORT ON BIOMETRICS
A maximum likelihood estimation and training on the fly approach
Biometric transaction confirmation with ComBiom.
Pace University IT691/Fall 2015
Presentation transcript:

A Study of the Channel Mismatch Problem in a Multimodal Face-Voice Biometric Access System FALLON SARATOVSKY, TODD EDWARDS, RICH KUITERS, HUGH ENG, AND HOMAYOON BEIGI SEIDENBERG SCHOOL OF CSIS, PACE UNIVERSITY

Overview  Key Terms  Background  Methodology  Results and Findings  Conclusion  References

Key Terms 1.Biometrics: The scientific analysis of one’s biological individuality, in order to identify and authenticate the individual in order to grant them access. ◦Biometrics matches implies the likelihood of exact validation. 2.Channel Mismatch: A common issue experienced within biometrics. Channel mismatch is caused by using devices that differ from the devices a user may have enrolled on. ◦Using an older or newer microphone, may affect authentication when participating in a speaker or speech recognition due to variations in microphone quality.

Key Terms 3.Enrollment: The first and most important part of the authentication process, because it sets the tone for any type of biometric system/recognition.

Key Terms 4.Multimodal Recognition: Multimodal recognition is the use of two or more options of authentication within a biometric system. ◦Example: a microphone for voice/speech recognition and a camera for facial recognition/liveliness test. ◦Multimodal biometric technologies offers the possibility for a more secure authentication process in biometrics.

Background Recognition Technologies, Inc. Recognition Technologies, Inc. Established in 2003 Established in 2003 Located in White Plains, NY Located in White Plains, NY Patented RecoMadeEasy® system is capable of open-set speaker recognition for large populations, widely considered to be one of the most difficult speaker recognition problems. Patented RecoMadeEasy® system is capable of open-set speaker recognition for large populations, widely considered to be one of the most difficult speaker recognition problems.

Background

Methodology Objectives: Objectives: Primary: Assess the enrollment and authentication processes with the use of a multimodal biometric system in order to determine various levels of channel mismatch. Primary: Assess the enrollment and authentication processes with the use of a multimodal biometric system in order to determine various levels of channel mismatch. Secondary: Evaluate any channel mismatch that may transpire during the authentication process of a multimodal biometric system with an external microphone. Secondary: Evaluate any channel mismatch that may transpire during the authentication process of a multimodal biometric system with an external microphone.

Methodology Method for Data Collection: Method for Data Collection: Data will be retrieved on site at Recongition Technologies, Inc. Testers will use the RecoMadeEasy system and application on two different Samsung devices (Samsung Galaxy Tab 4 and Samsung S6). Data will be retrieved on site at Recongition Technologies, Inc. Testers will use the RecoMadeEasy system and application on two different Samsung devices (Samsung Galaxy Tab 4 and Samsung S6). Participants will enroll on two separate devices and then try to authenticate on opposite devices. Participants will enroll on two separate devices and then try to authenticate on opposite devices. An external microphone will also be used to test for channel mismatch on the Samsung Galaxy Tab 4. An external microphone will also be used to test for channel mismatch on the Samsung Galaxy Tab 4.

Results and Findings Enrollment is the most important part of the authentication. Enrollment is the most important part of the authentication. Enrollment must be uniform for all users, and must be done in a controlled environment in order to create an even playing field for the authentication process. Enrollment must be uniform for all users, and must be done in a controlled environment in order to create an even playing field for the authentication process. Example: All users should enroll on the same device, all users should all users should be in a controlled environment, and all users should perform the same enrollment tests. Example: All users should enroll on the same device, all users should all users should be in a controlled environment, and all users should perform the same enrollment tests.

Conclusion Biometric software is constantly evolving and the goal is to eventually eliminate the use of standard passwords. Biometric software is constantly evolving and the goal is to eventually eliminate the use of standard passwords. Many industries have begun to implement biometric software, including many of our workplaces. Many industries have begun to implement biometric software, including many of our workplaces. Many of our own personal devices like cell phones, tablets, and laptops are being designed with integrated facial and fingerprint biometrics Many of our own personal devices like cell phones, tablets, and laptops are being designed with integrated facial and fingerprint biometrics There is still room for improvement with biometrics. There is still room for improvement with biometrics. The improvements should start with the enrollment process, since this is the first step in biometrics. The improvements should start with the enrollment process, since this is the first step in biometrics.

References [1] Beigi, H., Effects of time lapse on speaker recognition results. In Digital Signal Processing, 16th International Conference on IEEE, 2009, pp 1-6 [2] Beigi, H. Mobile Device Transaction Using Multi-Factor Authentication. Yorktown Heights, NY, 2011 [3] Beigi, H. “Speaker Recognition-Practical Issues.” Powerpoint, [4] Beigi, H., Recognition Technologies website, [5]Bush, G. “National Security Presidential Directive and Homeland Security Presidential Directive,” June 5, [6] Fang Zheng, T., Jin, Q., Li, L., Wang, J., Bie, F., “An Overview of Robustness Related Issues in Speaker Recognition”, 2014, pp 2-3 [7] Fernandez Gallardo, L., Wagner, M., Möller S., "I-vector Speaker Verification for Speech Degraded by Narrowband and Wideband Channels." Speech Communication; 11. ITG Symposium; Proceedings of. VDE, 2014 [8] Bonneau, J., Herley, C., Van Oorschot, P. C., Stajano, F., “Passwords and the Evolution of Imperfect Authentication.,” Communications of the ACM, vol. 58, no. 7, July 2015, pp. 78–87 [9] Jain, A., Nandakaumar, K., Ross, A., “Score normalization in multimodal biometric systems”, 2005, pp [10] Kinnunen, T., Speaker Recognition, Department of Computer Science - University of Joensuu, 2003 [11] Mazaira-Fernandez, L., Alvarez-Marquina, A., Gomez-Vilda, P., “Improving Speaker Recognition by Biometric Voice Deconstruction.” [12] Mishra, A., “Multimodal Biometrics it is: Need for Future Systems”. International Journal of Computer Applications,, June 2010, vol. 3, no. 4, pp [13] Pato, J., Millett, L., Whither Biometrics Committee. "Biometric Recognition: Challenges and Opportunities.", 2010, pp 9 [14] Pelecanos, J., Sridharan, S., “Feature Warping for Robust Speaker Verification”, 2001 [15] Petrovska-Delacretaz, D., Chollet, G., Guide to Biometric Reference Systems and Performance Evaluation, 2009, pp [16] Saquib, Z., Salam, N., Nair, R. P., Pandey, N., & Joshi, A., A survey on automatic speaker recognition systems. Signal Processing and Multimedia, 2010, pp [17] Scheffer, N., et al. "Recent developments in voice biometrics: Robustness and high accuracy." Technologies for Homeland Security (HST), 2013 [18] Doel, K.,“SplashData’s fifth annual ‘Worst Passwords List’ shows people continue putting themselves at risk.”, prweb, 2016 [19] Sreenivasa Rao, K., Sourjya, S., “Robust Speaker Recognition in Noisy Environments”, 2014, pp 8-9 [20] “Voice biometrics authentication across channels”, Nuance Communications, 2014 [21] Qi, X. Types of Biometrics. Web [22] Zhang, D., Automated biometrics: Technologies and systems (Vol. 7). Springer Science, 2013