Identity authentication based on keystroke latencies
Communications of the ACM
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Machine Learning - Special issue on learning with probabilistic representations
User authentication through keystroke dynamics
ACM Transactions on Information and System Security (TISSEC)
Input Feature Selection by Mutual Information Based on Parzen Window
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Benchmarking Attribute Selection Techniques for Discrete Class Data Mining
IEEE Transactions on Knowledge and Data Engineering
On the equalization of keystroke timing histograms
Pattern Recognition Letters
Toeplitz And Circulant Matrices: A Review (Foundations and Trends(R) in Communications and Information Theory)
Keystroke dynamics with low constraints SVM based passphrase enrollment
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
User authentication through typing biometrics features
IEEE Transactions on Signal Processing
Gaussian Mixture Modeling of Keystroke Patterns for Biometric Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Verification of computer users using keystroke dynamics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A parallel decision tree-based method for user authentication based on keystroke patterns
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Computer user verification using login string keystroke dynamics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An upper bound estimate on classification error (Corresp.)
IEEE Transactions on Information Theory
A class of upper bounds on probability of error for multihypotheses pattern recognition (Corresp.)
IEEE Transactions on Information Theory
Using mutual information for selecting features in supervised neural net learning
IEEE Transactions on Neural Networks
Using global knowledge of users' typing traits to attack keystroke biometrics templates
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security
On the complexity of aggregating information for authentication and profiling
DPM'11 Proceedings of the 6th international conference, and 4th international conference on Data Privacy Management and Autonomous Spontaneus Security
Examining a Large Keystroke Biometrics Dataset for Statistical-Attack Openings
ACM Transactions on Information and System Security (TISSEC)
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Heterogeneous and aggregate vectors are the two widely used feature vectors in fixed text keystroke authentication. In this paper, we address the question ''Which vectors, heterogeneous, aggregate, or a combination of both, are more discriminative and why?'' We accomplish this in three ways - (1) by providing an intuitive example to illustrate how aggregation of features inherently reduces discriminability; (2) by formulating ''discriminability'' as a non-parametric estimate of Bhattacharya distance, we show theoretically that the discriminability of a heterogeneous vector is higher than an aggregate vector; and (3) by conducting user recognition experiments using a dataset containing keystrokes from 33 users typing a 32-character reference text, we empirically validate our theoretical analysis. To compare the discriminability of heterogeneous and aggregate vectors with different combinations of keystroke features, we conduct feature selection analysis using three methods: (1) ReliefF, (2) correlation based feature selection, and (3) consistency based feature selection. Results of feature selection analysis reinforce the findings of our theoretical analysis.