Enrique P. Calot

Laboratorio de Sistemas de Información Avanzados · UBA

The data presented in this article comprises human-written samples of keystroke dynamic features for free-text inputs, in the form of sentences written in natural language, together with synthesized samples that share the same text sequences. The human-written samples originate in three publicly available datasets that have been previously used in...

While the accuracy of keystroke dynamics verification systems has traditionally been evaluated using a zero-effort attack model, the current trend is to recognize that such an approach is too optimistic. Attacks using statistical models and synthetic forgeries have been shown to achieve significant rates of success, motivating the study of methods...

Keystroke dynamics is a soft biometric trait. Although the shape of the timing distributions in keystroke dynamics profiles is a central element for the accurate modeling of the behavioral patterns of the user, a simplified approach has been to presuppose normality. Careful consideration of the individual shapes for the timing models could lead to...

The internal correlation of timing features inside word boundaries of free text sessions are studied, together with the classification performance in both authentication and identification tasks, using three publicly available datasets. Increasing distance between keystrokes was not found to be predictive of decreased correlation, even when individ...

Keystroke dynamics facilitates the identification of a person by the way they type. This article focuses on analysing the robustness of keystroke dynamics algorithms against variations in biometric records through electroencephalography, using waves associated with states of relaxation and excitement and a self-report questionnaire. An experiment w...

This paper explores the use of genetic algorithms in identifying effective lies for use in negotiations with incomplete information in State Oriented Domains (SOD's). The aim is to seek lies which are not just safe (i.e. they will not lead to a disgraceful outcome) but also yield the highest possible utility. In this work a GAs based representation...

Breast cancer is a very common disease and the cause of death of many people. It has been proven that prevention decreases the death rate, but the costs of diagnosis and image processing are very high when applied to all the population with potential risk. This paper studies an existent computer aided diagnosis method using neural network and impro...

The Repertory Grid method is widely used in knowledge engineering to infer functional relationships between constructs given by an expert. The method is ignoring information that could be used to infer more precise dependencies. This paper proposes an improvement to take advantage on the information that is being ignored in the current method. Furt...

Resumen La aplicación de sistemas inteligentes a áreas de la medicina es aún un campo abierto a la investigación. Este artículo propone una mejora a la metodología que aplica redes neuronales para clasificar tumores en mamografías de manera automática. Para esto se procederá a introducir un filtro Sobel sobre la imagen preprocesada para así obtener...

This paper explores the use of genetic algorithms in identifying effective lies for use in negotiations with incomplete information in State Oriented Domains (SOD's). The aim is to seek lies which are not just safe (i.e. they will not lead to a disgraceful outcome) but also yield the highest possible utility. We propose a representation of a goal,...