Comparison of computer attacks: an application of interval-based fuzzy integration

In recent years, there has been a huge increase in the number of reported computer attacks. Hacking skills are not even necessary anymore. Therefore, network and system protection have become critical issues for companies. In order to know how to protect a system, we need to understand what impact an attack may have, and more specifically, we need to order attacks in terms of their impact on the system to be protected. To do so, attacks have to be classified with respect to a set of well defined criteria or attributes. This paper shows how we can use 2-additive measures and integrals, that take interval monodimensional utility functions as inputs, and have interval values can be used as accurate aggregation operators to classify network attacks. Yet, the use of 2-additive measures, instead of more general fuzzy measures allows us to keep the complexity of the problem under control in O(n²).