Modern military systems operated with a complex of computers and software may have mission failure which is caused by undetected attacks. In such situations, it is important to find out which assets are damaged. After identifying damaged assets, we need to immediately examine the damaged assets to defend against the attacks. However, it is not straightforward to explore the damaged assets because there are the complicated relationships among assets, tasks and missions. In this paper, we propose an effective methodology to infer the damaged assets given observed mission impacts in a Bayesian framework. We used Bayesian networks to model assets, tasks, missions and to set the relationships among them. Our approach visually infers and identifies the damaged assets with the probability. We show that proposed Bayesian framework is practical and useful with the use case experiment.
|Title of host publication||Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers|
|Editors||Brent ByungHoon Kang, JinSoo Jang|
|Number of pages||12|
|Publication status||Published - 2019|
|Event||19th World International Conference on Information Security and Application, WISA 2018 - Jeju Island, Korea, Republic of|
Duration: 2018 Aug 23 → 2018 Aug 25
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||19th World International Conference on Information Security and Application, WISA 2018|
|Country/Territory||Korea, Republic of|
|Period||18/8/23 → 18/8/25|
Bibliographical notePublisher Copyright:
© Springer Nature Switzerland AG 2019.
Copyright 2019 Elsevier B.V., All rights reserved.
- Bayesian network
- Cyber warfare
- Mission impact assessment
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)