Visual Exploration of Network Hostile Behavior
Jorge Guerra, Carlos Adrian Catania, Eduardo Enrique Veas · 2017
This paper presents a graphical interface to identify hostile behavior in network logs. The problem of identifying and labeling hostile behavior is well known in the network security community. There is a lack of labeled datasets, which make it difficult to deploy automated methods or to test the performance of manual ones. We describe the process of searching and identifying hostile behavior with a graphical tool derived from an open source Intrusion Prevention System, which graphically encodes features of network connections from a log-file. A design study with two network security experts illustrates the workflow of searching for patterns descriptive of unwanted behavior and labeling occurrences therewith.