1. Mouse Movement Biometrics, Pace University, Fall'20071 Mouse Movement Biometrics Fall 2007 Capstone -Team Members Rafael Diaz Michael Lampe Nkem Ajufor Mohammed Islam Antony Amalraj

2. Mouse Movement Biometrics, Pace University, Fall'20072 Mouse Movement Biometrics - Agenda of Final Presentation Brief Scope of the project Brief Scope of the project Project Requirements and Specification Project Requirements and Specification Design Decisions Design Decisions Objectives Objectives Demonstration of MMSystem Demonstration of MMSystem Testing Strategy Testing Strategy Meetings Format Meetings Format Challenges Challenges Wrap up/Summary of Accomplishments Wrap up/Summary of Accomplishments Recommendations Recommendations Questions Questions

3. Mouse Movement Biometrics, Pace University, Fall'20073 Mouse Movement Biometrics Brief Scope of the project This semester's project had two primary focuses. This semester's project had two primary focuses. –First, we became familiar with the system and collected as much additional data as possible, including data from each team member and third party data –Second, and most importantly, we formatted the feature-vector data for ease of processing by other back-end teams, by normalizing feature-vector data.

4. Mouse Movement Biometrics, Pace University, Fall'20074 Mouse Movement Biometrics Project Requirements Capture data of individual mouse user (a total of 50 data files) Capture data of individual mouse user (a total of 50 data files) –Mouse Movement –Mouse Click Generate corresponding feature data in normalized feature format for the backend teams Generate corresponding feature data in normalized feature format for the backend teams Perform calculations to quantify mouse movements Perform calculations to quantify mouse movements Obtain recognition accuracy (just first-choice nearest neighbor) using the leave-one-out procedure on the 50 data files. Obtain recognition accuracy (just first-choice nearest neighbor) using the leave-one-out procedure on the 50 data files.

5. Mouse Movement Biometrics, Pace University, Fall'20075 Mouse Movement as a Biometric Measurement - Specifications Mouse Movement data was captured through the enrollment process and the creation of a user profile Mouse Movement data was captured through the enrollment process and the creation of a user profile The intent of data capturing is to identify the user based on the stored data and the data that was recently captured The intent of data capturing is to identify the user based on the stored data and the data that was recently captured This method of identification, in which the data recently captured is compared to the information on the database, is known as a One to Many comparison This method of identification, in which the data recently captured is compared to the information on the database, is known as a One to Many comparison Throughout this phase of the project the data captured and used was validated with both the K- Nearest Neighbor and Leave One Out methods Throughout this phase of the project the data captured and used was validated with both the K- Nearest Neighbor and Leave One Out methods Below are some of the focus points in this Mouse Movement Study: Below are some of the focus points in this Mouse Movement Study: –Obtain data while user clicking buttons or enrolling user info –Capture the data in a CSV format for normalization purposes –Generate feature extraction data from feature extractor module. –Classify user and possible identification using classifier –Send a set of normalized data to backend teams and Generate success statistics success statistics

6. Mouse Movement Biometrics, Pace University, Fall'2007 6 Mouse Movement Biometrics – Design decisions Mouse Movement Biometric System Data and User Mouse action data, GUI changes Data Storage csv files Feature Vector Extraction and Profile creation Normalization Classifies the feature vector. Finds the nearest neighbors User Mouse action data Enrollment Mode Identification Result Success Statistics

7. Mouse Movement Biometrics, Pace University, Fall'20077 Mouse Movement Biometrics – Objectives We reported a total of 205 data files - including the data generated by 3 rd parties We reported a total of 205 data files - including the data generated by 3 rd parties Generated normalized feature vector data files and passed it on to the backend teams (Team 5 and 6) Generated normalized feature vector data files and passed it on to the backend teams (Team 5 and 6) Obtained recognition accuracy (first-choice nearest neighbor – 80%) using the leave-one-out procedure using 35 data files. Obtained recognition accuracy (first-choice nearest neighbor – 80%) using the leave-one-out procedure using 35 data files. Obtained results from KNN method using Classifier Module. Obtained results from KNN method using Classifier Module.

8. Mouse Movement Biometrics, Pace University, Fall'20078 Mouse Movement Biometrics - Objectives cont’d Generated Data at weekly intervals - 205 files total, including 3 rd party data Generated Data at weekly intervals - 205 files total, including 3 rd party data –Data from more subjects –Data from random button sequences Enhanced mmsystem module has been developed with rich GUI features for the future users. Enhanced mmsystem module has been developed with rich GUI features for the future users. It also will generate an additional file called profile.txt along with Raw data files. It also will generate an additional file called profile.txt along with Raw data files. –This Profile.txt file will be used as an input for both feature extraction and classifier module. The team created a website to ensure all our documents, course software will be uploaded in a centralized location. The team created a website to ensure all our documents, course software will be uploaded in a centralized location.

9. Mouse Movement Biometrics, Pace University, Fall'20079 Mouse Movement Biometrics - Objectives cont’d Enhancement of the existing front-end registration process that captures pertinent information regarding the user Enhancement of the existing front-end registration process that captures pertinent information regarding the user –User Name –Output File Name –Gender >> Male or Female –Age –Right- handed or Left- handed –Type of Mouse

10. Mouse Movement Biometrics, Pace University, Fall'200710 Mouse Movement Biometrics - User Input GUI Input Dialog Box #1 Enter User Name Input Dialog Box #2 Enter File Name Input Dialog Box #3 Select your Gender ( Male / Female ) Input Dialog Box #4 Select your age ( 18-50 or N/A )

11. Mouse Movement Biometrics, Pace University, Fall'200711 Mouse Movement Biometrics - User Input: Continued Input Dialog Box #5 Select your hand used ( Right-handed / Left Handed ) Input Dialog Box #6 Select type of mouse ( Optical Mouse / Serial Mouse USB Mouse / Wireless Mouse ) Input Dialog Box #7 Select type of Test Screen ( Fixed 25 button sequence, Tic-Tac-Toe Game, or Blank Screen )

12. Mouse Movement Biometrics, Pace University, Fall'200712 Mouse Movement Biometrics - User Input GUI: to be continued

13. Mouse Movement Biometrics, Pace University, Fall'200713 Mouse Movement Biometrics-Normalized Feature Vector Report

14. Mouse Movement Biometrics, Pace University, Fall'200714 Mouse Movement Biometrics – Demonstration of Enhanced System Demonstration of the enhanced mouse movement (old mmsystem and new mmsystem) provide recommendations Demonstration of the enhanced mouse movement (old mmsystem and new mmsystem) provide recommendations Overview of the Technical paper Overview of the Technical paper

15. Mouse Movement Biometrics, Pace University, Fall'200715

16. Mouse Movement Biometrics, Pace University, Fall'200716 Mouse Movement Biometrics Testing strategy Validation of the new code introduced to correct and address any bugs identified in the testing window Validation of the new code introduced to correct and address any bugs identified in the testing window Corrections to program/bugs done by team members after response/comments received from team and volunteers that ran the application Corrections to program/bugs done by team members after response/comments received from team and volunteers that ran the application For program data, all members input 5 samples of data and data was validated through the classifier program For program data, all members input 5 samples of data and data was validated through the classifier program

17. Mouse Movement Biometrics, Pace University, Fall'200717 Mouse Movement Biometrics - Meeting Format Team 1 met twice a week via a conference bridge – Tuesdays and Fridays Team 1 met twice a week via a conference bridge – Tuesdays and Fridays –Tuesday’s meeting was focused on the team and the overall status of the project –Friday’s meeting was focused on questions that were presented to the client All conference calls lasted 1 hour in duration All conference calls lasted 1 hour in duration Communication via e-mail was also used and all involved parties were copied on the e-mails. Communication via e-mail was also used and all involved parties were copied on the e-mails.

18. Mouse Movement Biometrics, Pace University, Fall'200718 Mouse Movement Biometrics – Wrap up/Summary of Accomplishments  Captured raw data in a CSV format for normalization and experiments  Generated Feature vector extraction data and Normalized Feature Vector  Generated Data in Mushroom data format for data mining project  Classified the users by KNN method and Leave One Out method  Generated Classified output data and Success statistics Report  Enhanced software modules to incorporate the GUI changes  Generated the data in the required format  Created Mouse Movement Biometrics Technical Paper  Created a User Manual to document use of the software  Created website to store the current application modules, tested results  Created training videos for the three applications in order to assist users in learning the system.  Uploaded the Technical Paper, User Manual as well as the mid term and final presentations on the website

19. Mouse Movement Biometrics, Pace University, Fall'200719 Mouse Movement Biometrics – Challenges During the initial enrollment process questions surrounding the application and how to access and run the application existed During the initial enrollment process questions surrounding the application and how to access and run the application existed Difficulties in understanding the normalization process and using only two values (0 and 1) Difficulties in understanding the normalization process and using only two values (0 and 1) Getting the enhancements made for the existing MMSystems GUI to work in a single display window Getting the enhancements made for the existing MMSystems GUI to work in a single display window

20. Mouse Movement Biometrics, Pace University, Fall'200720 Mouse Movement Biometrics - Recommendations Further enhancements to the data Capture module. Further enhancements to the data Capture module. – Work was started on adding new data fields to the Feature Extraction and Classifier modules but will need to be continued by succeeding teams. While 100% accuracy is not probable, it seems more experiments need to be performed to see if there is a more consistent accuracy rate over time and from more generated data. While 100% accuracy is not probable, it seems more experiments need to be performed to see if there is a more consistent accuracy rate over time and from more generated data. Subsequent teams should focus on developing the Data Capture GUI to randomize the buttons to provide more varied data Subsequent teams should focus on developing the Data Capture GUI to randomize the buttons to provide more varied data

21. Mouse Movement Biometrics, Pace University, Fall'200721 Mouse Movement Biometrics – Recommendations cont’d Subsequent teams can add more user characteristics to classify the user Subsequent teams can add more user characteristics to classify the user Also, Subsequent teams can add more characteristics of the mouse such as right click or track wheel use Also, Subsequent teams can add more characteristics of the mouse such as right click or track wheel use Finally, it would be optimal if the system was developed to be used online with a database backend. Finally, it would be optimal if the system was developed to be used online with a database backend. –This would allow for more data to be generated from a larger pool of users for further analysis and research.

22. Mouse Movement Biometrics, Pace University, Fall'200722 Questions/Comments http://utopia.csis.pace.edu/cs691/2007- 2008/team1/default.htm http://utopia.csis.pace.edu/cs691/2007- 2008/team1/default.htm http://utopia.csis.pace.edu/cs691/2007- 2008/team1/default.htm http://utopia.csis.pace.edu/cs691/2007- 2008/team1/default.htm