Learn More
The binary feature vector is one of the most common representations of patterns and measuring similarity and distance measures play a critical role in many problems such as clustering, classification, etc. Ever since Jaccard proposed a similarity measure to classify ecological species in 1901, numerous binary similarity and distance measures have been(More)
A long-text-input keystroke biometric system was developed for applications such as identifying perpetrators of inappropriate e-mail or fraudulent Internet activity. A Java applet collected raw keystroke data over the Internet, appropriate long-text-input features were extracted, and a pattern classifier made identification decisions. Experiments were(More)
A novel keystroke biometric system for long-text input was developed and evaluated for user identification and authentication applications. The system consists of a Java applet to collect raw keystroke data over the internet, a feature extractor, and pattern classifiers to make identification or authentication decisions. Experiments on over 100 subjects(More)
Over the last six years Pace University has been developing a long-text-input keystroke biométrie system. The system consists of three components: a java applet that collects raw keystroke data over the Internet, a feature extractor, and a pattern classifier. This paper presents two significant system improvements. The first achieves high performance(More)
or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or to republish, requires a fee and/or special permission from JPRR. Abstract Similarity and dissimilarity(More)
Tree-based classifiers are important in pattern recognition and have been well studied. Although the problem of finding an optimal decision tree has received attention, it is a hard optimization problem. Here we propose utilizing a genetic algorithm to improve on the finding of compact, near-optimal decision trees. We present a method to encode and decode a(More)
This study focuses on the development and evaluation of a new classification algorithm that halves the previously reported best error rate. Using keystroke data from 119 users, closed system performance was obtained as a function of the number of keystrokes per sample. The applications of interest are authenticating online student test takers and computer(More)
Most e-mail readers spend a non-trivial amount of time regularly deleting junk e-mail (spam) messages, even as an expanding volume of such e-mail occupies server storage space and consumes network bandwidth. An ongoing challenge, therefore, rests within the development and refinement of automatic classifiers that can distinguish legitimate e-mail from spam.(More)
Quantitatively establishing the discriminative power of iris biometric data is considered. Multi-level 2D wavelet transform has been widely used for iris verification system. While previous approaches compute only means and variances, we propose using a his-togram distance. We also use a methodology to establish a measure of discrimination that is(More)