Assessment of extended aggregated association rules

In this paper we discuss some issues related to generating aggregated association rules which implies the fact that features can take on values from finite sets with any number of elements, not only binary ones. We consider changes in the structure of a rule and the influence of these changes on some association rule parameters. We note that considering rules with low values of the main rule parameters can be of a great importance for resolving security problems. These results can be used by specialists in Big Data processing.