TY - GEN
T1 - A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack
AU - Shim, Shinwoo
AU - Yoon, Ji Won
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Bayesian network
KW - Cyber warfare
KW - Mission impact assessment
UR - http://www.scopus.com/inward/record.url?scp=85065040079&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065040079&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-17982-3_15
DO - 10.1007/978-3-030-17982-3_15
M3 - Conference contribution
AN - SCOPUS:85065040079
SN - 9783030179816
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 185
EP - 196
BT - Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers
A2 - Kang, Brent ByungHoon
A2 - Jang, JinSoo
PB - Springer Verlag
T2 - 19th World International Conference on Information Security and Application, WISA 2018
Y2 - 23 August 2018 through 25 August 2018
ER -