A Taxonomy of Malicious Traffic for Intrusion Detection Systems
This work addresses the need for standardized attack classification in network security for researchers, but it is incremental as it builds on existing taxonomies without introducing new detection methods.
The authors tackled the problem of inconsistent classification of network attacks by proposing a taxonomy to help design better intrusion detection systems, resulting in a structured framework for researchers to focus on creating accurate systems and datasets.
With the increasing number of network threats it is essential to have a knowledge of existing and new network threats in order to design better intrusion detection systems. In this paper we propose a taxonomy for classifying network attacks in a consistent way, allowing security researchers to focus their efforts on creating accurate intrusion detection systems and targeted datasets.