Name
Abstract | ||
|---|---|---|
Incident prioritization is nowadays a part of many approaches and tools for network security and risk management. However, the dynamic nature of the problem domain is often unaccounted for. That is, the prioritization is typically based on a set of static calculations, which are rarely adjusted. As a result, incidents are incorrectly prioritized, leading to an increased and misplaced effort in the incident response. A higher degree of automation could help to address this problem. In this paper, we explicitly consider flaws in the prioritization an unalterable circumstance. We propose an adaptive incident prioritization, which allows to automate certain tasks for the prioritization model management in order to continuously assess and improve a prioritization model. At the same time, we acknowledge the human analyst as the focal point and propose to keep the human in the loop, among others by treating understandability as a crucial requirement. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CyberSecPODS.2019.8885208 | 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security) |
Keywords | Field | DocType |
incident prioritization,network security,cyber security,adaptive learning | Anomaly detection,Telecommunications network,Task analysis,Problem domain,Computer science,Network security,Automation,Risk analysis (engineering),Risk management,Human-in-the-loop | Conference |
ISBN | Citations | PageRank |
978-1-7281-0230-6 | 0 | 0.34 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonard Renners | 1 | 4 | 2.74 |
| Felix Heine | 2 | 0 | 1.69 |
| Carsten Kleiner | 3 | 73 | 21.21 |
| Gabi Dreo Rodosek | 4 | 134 | 44.97 |