Biometric Data MiningBiometric Data Mining

“A Data Mining Study of Mouse Movement, Stylometry, and Keystroke Biometric Data”

Clara Eusebi, Cosmin Gilga, Deepa John, Andre Maisonave.

Presentation SummaryPresentation Summary

Project DescriptionExperiment StructureAlgorithms and TechniquesResults of ExperimentsFuture ResearchConclusions

Project DescriptionProject Description

The study extends previous studies at Pace University on Biometric data by running previously obtained data sets through a data mining tool called Weka, using various algorithms and techniques.

Study ExperimentsStudy ExperimentsAuthentication

◦Dichotomy model

Identification◦Normalized data

Additional◦Normalized data

Algorithms and Algorithms and TechniquesTechniquesAuthentication

◦IBk with k = 1 on Dichotomy dataIdentification

◦IBk with k = 1 on Normalized dataAdditional

◦PredictiveApriori◦simpleKmeans◦IBk with k = 1 using leave-one-out

and percentage splits

ResultsResultsTrain Test Type Accuracy

1(5 samples

from each of 4 subjects)

2(5 samples

from each of 4 subjects)

Copy Desktop 95.79%

Free Desktop 96.32%

Copy Laptop 91.58%

Free Laptop 92.11%

1(5 samples

from each of 4 subjects)

3(5 samples

from each of 4 subjects)

Copy Desktop 88.95%

Free Desktop 98.42%

Copy Laptop 100.00%

Free Laptop 93.68%

Results of Longitudinal Authentication Experiments on new Keystroke Capture Data

ResultsResultsTrain Test Type Accuracy

1(5 samples

from each of 4 subjects)

2(5 samples

from each of 4 subjects)

Copy Desktop 95%

Free Desktop 100%

Copy Laptop 100%

Free Laptop 85%

1(5 samples

from each of 4 subjects)

3(5 samples

from each of 4 subjects)

Copy Desktop 80%

Free Desktop 100%

Copy Laptop 100%

Free Laptop 100%

Results of Longitudinal Identification Experiments on the new KeystrokeCapture Data.

Opportunities for Opportunities for ResearchResearchAuthentication based solely on

subject in question. Separate sets of data holding only within

and between class records for each subject,

Rather than comparing a community of subjects to a community of records.

Higher accuracies could be legitimately obtained in this manner.

ConclusionConclusionThe study has furthered previous studies at

Pace University through running experiments on Mouse Movement, Stylometry, and Keystroke Biometric data, new and previously obtained, using the data mining tool Weka.

The data mining algorithms with which the experiments were conducted are widely used and provide an entry point for future researchers into the use of data mining with biometric data sets.