A Biometrics-embedded System Based on Haptics for User Authentication in Virtual Environments

1. A Biometrics-embedded System Based on Haptics for User Authentication in Virtual Environments Presented by Mauricio Orozco October 2007 University Of Ottawa SITE/EITI

2. Outline • Introduction • Contributions • Research Statement • Outline Architecture • Methodology • Conclusions • Future Work

3. Contributions • Design and development of a procedure for: • Combining haptic technology to discriminate human-hand psychomotor • patterns to be used for authentication/verification purposes • Analysis and definition of features and feature set • Haptic data to be used as biometric identifiers to characterize the human • Interaction behaviour • The amount of information contained in an individual’s features characterizes • (i.e. Force and Torque )the uniqueness of an individual • The user behavior exhibited in Virtual Domains should be modeled as • “entropic signatures” according to features that areconsistently unique • for each user • Results suggest that haptic-based biometrics are best suited toverification • At 25% False Acceptance Rate (FAR), the Probability of Verification (PV) for • haptic-based Application (i.e. “maze”) identification was at best 75.5%, • While the PV of verification system was at best 98%

4. Publications from this thesis Papers in refereed Journals • Mohamad Eid, Mauricio Orozco and Abdulmotaleb El Saddik, "A Guided Tour in Haptic Audio Visual Environment and Applications", Int. J. of Advanced Media and Communication. Vol.1 (3), 2007 • Abdulmotaleb El Saddik, Mauricio Orozco, Yednek Asfaw, Shervin Shirmohammadi and Andy Adler, "A Novel Biometric System for Identification and Verification of Haptic Users", IEEE Transactions on Instrumentation and Measurement, vol.56 (3) 2007. • Mauricio Orozco, Matthew Graydon, Shervin Shirmohammadi, and Abdulmotaleb El Saddik, "Experiments in Haptic-Based Authentication of Humans", Journal of Multimedia Tools and Applications, 2007 • Mauricio Orozco and Abdulmotaleb El Saddik “AdHapticA” IEEE Transactions on Instrumentation and Measurement, accepted to appear in 2008 Papers in refereed Conferences • Mauricio Orozco, Matthew Graydon, Shervin Shirmohammadi and Abdulmotaleb El Saddik, "Using Haptic Interfaces for User Verification in Virtual Environments", In proceedings of the 2006 IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Spain, July 2006. • Ismail Shakra, Mauricio Orozco, Abdulmotaleb El Saddik, Shervin Shirmohammadi, Edward Lemaire, "VR-Based Hand Rehabilitation using a Haptic-Based Framework", In proceedings of the 2006 IEEE Instrumentation and Measurement Technology Conference (IMTC/06), Sorrento, Italy, 24 - 27 April 2006. • Ismail Shakra, Mauricio Orozco, Abdulmotaleb El Saddik, Shervin Shirmohammadi, Edward Lemaire, "Haptic Instrumentation for Physical Rehabilitation of Stroke Patients", In proceedings of the 2006 IEEE International Workshop on Medical Measurement and Applications Benevento, Italy 20 - 21 April 2006. • Mauricio Orozco, Yednek Asfaw, Shervin Shirmohammadi, Andy Adler, and Abdulmotaleb El Saddik, "Haptic-Based Biometrics: A Feasibility Study", In Proceedings of the IEEE VR 2006, pp. 265 - 271, March 25-29, Alexandria, Virginia, USA, 2006. • Yednek Asfaw, Mauricio Orozco, Shervin Shirmohammadi, Abdulmotaleb El Saddik, Andy Adler, "Participant Identification in Haptic systems using HMMs", In Proceedings of the fourth IEEE International Workshop on Haptic Virtual Environments and their Applications (HAVE2005)", pp. 127 -132 2005. • Mauricio Orozco and Abdulmotaleb El Saddik, "Haptic: The New Biometrics-embedded Media to Recognizing and Quantifying Human Patterns" In proceedings of 13th Annual ACM International Conference on Multimedia (ACM-MM 2005), Singapore, November 06-12, 2005. • Mauricio Orozco , Ismail Shakra and Abdulmotaleb El Saddik, “Adaptive Haptic Framework”, In proceedings of the IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Giardini Naxos, Italy, 18-20 July 2005. • Mauricio Orozco and Abdulmotaleb El Saddik, “Signature Identification with Haptic devices”, In proceedings of the IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems, Giardini Naxos, Italy, 18-20 July 2005. • Mauricio Orozco, Yednek Asfaw, Andy Adler, Shervin Shirmohammadi, and Abdulmotaleb El Saddik, “Automatic Identification of Participants in Haptic Systems”, In proceedings of the 2005 IEEE Instrumentation and Measurement Technology Conference (IMTC/05), Ottawa, Ontario, Canada, 17-19 May 2005.

5. Level of Interaction Haptic Technology & Apps Haptics Telephony Letters Time Telepresence +Haptics Biometric Technology & Apps Biometrics Internet Source: International Biometric Group, New York, NY Motivation

6. Time 2D Position 3D Position Force Pressure Angular orientation Torque Velocity Keyboard Mouse CyberGlove Digital Tablet Haptics Why Use Haptics?

7. Introduction Haptic Systems Biometrics Systems

8. Research Statement H1: The quantitative performance of specific haptic interface lies significantly in acceptable range to be considered as biometric identifier system H0: The quantitative performance of specific haptic interface does not lie significantly in acceptable range to be considered as biometric identifier system ?

9. Dynamic Signature Verification [Fernandez et al, 2005],[Plamondon, 1990], …plenty Keystroke Dynamics Behavioural Biometrics [ Joyce and Gupta , 1990] [ Umpresh and Williams, 1985] [Obaidat and Sadoun,1997] and more Mouse :DSV CyberGlove:DataGlove [Everitt and McOwan, 2003] [Everitt and McOwan, 2003] Related Work: Behavioral Biometrics

10. Methodology Feature Generation Adaptive Haptic Framework Selection / Classifier Design / Evaluation Haptic - Based Applications Feature Generation : + Virtual Maze + K - means + Virtual Cheque x = { Vx , Vy , Vz , ... } + Neural Networks + Virtual Phone + PCA + DTW Preprocessing + Nearest Neighbor Feature Selection : System Evaluation + Relative Entropy Matching Score Behavioural DAO Data Acquisition Repository Proposed Approach: AdHapticA

11. Feature Generation Adaptive Haptic Framework Selection / Classifier Design / Evaluation Haptic - Based Applications Feature Generation : + Virtual Maze + K - means + Virtual Cheque x = { Vx , Vy , Vz , ... } + Neural Networks + Virtual Phone + PCA + DTW Preprocessing + Nearest Neighbor Feature Selection : System Evaluation + Relative Entropy Matching Score Behavioural DAO Data Acquisition Repository Methodology Proposed Approach: AdHapticA

12. Applications Single Point Interaction PHANToM Haptic Desktop Multiple Point Interaction CyberGrasp Unit Haptic-Based Applications

13. Feature Generation Selection / Classifier Design / Evaluation Haptic - Based Applications Feature Generation : + Virtual Maze + K - means + Virtual Cheque x = { Vx , Vy , Vz , ... } + Neural Networks + Virtual Phone + PCA + DTW Preprocessing + Nearest Neighbor Feature Selection : System Evaluation + Relative Entropy Matching Score Behavioural DAO Data Acquisition Repository Methodology Proposed Approach: AdHapticA Adaptive Haptic Framework

14. Data Acquisition Database consists ~ 109 volunteers ( > 2 year ) Each providing 10 genuine samples: + Handwritten signature + Maze solved + Dialled telephone codes Participants were given the opportunity to practice each application before Each process recorded among others parameters the pen’s position(x,y,z), force applied (N) and device angle (φ)

15. DTW( Dynamic Time Warping Functional Approach Spectral Analysis (FFT) K-Means Single Point Interaction Parametric Approach Majority Class. HAPTIC DEVICE Euclidean Distance Multiple Point Interaction Neural Networks Information Content Analysis

16. Validation Scheme Maze Performance Dynamic Time Warping Equal Error Rate (EER)22.3% with a threshold Matching Score of 0.195 Functional Approach Spectral Analysis:FFT

17. Virtual Cheque Feature Set: 35 Variables Validation Scheme Majority Rule Maze Performance Equal Error Rate (EER) of 6.0% with a threshold of 1.6 for the best (Cheque ) Virtual MobilePhone Parametric Approach

18. To measure the uncertainty associated with a random variable Analysis of the Haptic Information Content • Advantages of Using Relative Entropy • Quantifies the information contained in a piece of data: in bits (if using base-2 logarithms) • Another distinct advantage of using relative entropy as a measure of biometric feature uniqueness is that it accounts for both the mean and variance of a distribution • The Relative or Shannon entropy is a measure of the average information content the recipient

19. The information content of biometric features differ amongst users of the haptic Entropic signature characterizes the identity of an individual by how unique their features are User 3 User 4 User 2 User 5 User 6 User 7 From a geometrical perspective, an entropic signature can be modeled as a curve in the plane User 10 User 8 User 9 Analysis :Information Content

20. Equal Error Rate EER=4.5% Verification Performance Identification EER=27% Authetication with Analysis of Information Content

21. User Entropic Signature RelativeEntropy Majority Rule accept 95.5% +/- 2.5% Analysis of System Security accept 19.14% +/- 3.5% Entropic Signature Conclusions

22. Future Work • Incorporating adaptive feedback between the feature extraction and the feature selection • Reducing the size of haptic data • Combining with other Biometrics • Embedded in Game-like environment

23. Thank you  Ευχαριστώ 谢谢 DMnvwd Dankie go raibh maith agaibh ありがとう متشکرم WAD MAHAD SAN TAHAY GADDA GUEY Asante Urakoze

24. Feedback • On 1/9/07, Eamonn Keogh <eamonn@cs.ucr.edu> wrote: Hello, I have read your nice paper [a]. You can make DTW significantly more accurate for this problem just by constraining the warping, see [b] or [c] :Professor from University of California USA. • IEEE-VR Symposium in Virginia USA, March 2006 The main contribution of the paper is that user identification can be possible in haptic manipulation task using several statistical analyses. However the result is affected by training existence or nonexistence, so this can be a disadvantage for haptic systems without trained users, or those where the user doesn’t frequently interact with the application • IEEE-HAVE Ottawa, Ontario, October 2005 Reviewer If the authors could show that the error rates are larger without the presence of haptics, then it might prove that the haptics are actually allowing greater behavioral variation, rather than less. For example, what if the subjects were asked to navigate the same maze with the haptic feedback turned off?