In this article, we propose a mathematical model, fundamentally based on evidence theory in
order to process and to combine the information elements coming from different sources of
information in a security system. These elements could be heteroge
neous (qualitative,
quantitative, ordinal, binary … etc.) and imperfect (imprecise, ambiguous, probable, missing
values … etc.). Along with the heterogeneity and the imperfection, we must consider the case
bases that contain security cases with solutions to help us to make decisions as supplementary
sources of information (this is called in machine learning field ''case-based reasoning'').
Furthermore, the proposed method must consider the conflict and the contradictory resulting
from the different sources of evidence. The afore-mentioned issues will be explained through an
illustrative numeric example to clarify the proposed model.
