This paper aims at proposing a methodology for evaluating current IDS capabilities of detecting attacks targeting the networks and their services. This methodology tries to be as r...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
— The increasing heterogeneity, dynamism, and uncertainty of emerging DCE (Distributed Computing Environment) systems imply that an application must be able to detect and adapt t...
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Cast shadows induced by moving objects often cause serious problems to many vision applications. We present in this paper an online statistical learning approach to model the backg...