A Semantic Approach for Automatic Structuring and Analysis of Software Process Patterns

The main contribution of this paper, is to propose a novel semantic approach based on a Natural Language Processing technique in order to ensure a semantic unification of unstructured process patterns which are expressed not only in different formats but also, in different forms. This approach is implemented using the GATE text engineering framework and then evaluated leading up to high-quality results motivating us to continue in this direction.

Hybrid Intrusion Detection and Prediction multiAgent System HIDPAS

This paper proposes an intrusion detection and prediction system based on uncertain and imprecise inference networks and its implementation. Giving a historic of sessions, it is about proposing a method of supervised learning doubled of a classifier permitting to extract the necessary knowledge in order to identify the presence or not of an intrusion in a session and in the positive case to recognize its type and to predict the possible intrusions that will follow it. The proposed system takes into account the uncertainty and imprecision that can affect the statistical data of the historic. The systematic utilization of an unique probability distribution to represent this type of knowledge supposes a too rich subjective information and risk to be in part arbitrary. One of the first objectives of this work was therefore to permit the consistency between the manner of which we represent information and information which we really dispose.