A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack

Shinwoo Shim; Ji Won Yoon

doi:10.1007/978-3-030-17982-3_15

A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers
Editors	Brent ByungHoon Kang, JinSoo Jang
Publisher	Springer Verlag
Pages	185-196
Number of pages	12
ISBN (Print)	9783030179816
DOIs	https://doi.org/10.1007/978-3-030-17982-3_15
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

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11402 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th World International Conference on Information Security and Application, WISA 2018
Country/Territory	Korea, Republic of
City	Jeju Island
Period	18/8/23 → 18/8/25

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

Keywords

Bayesian network
Cyber warfare
Mission impact assessment

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-17982-3_15

Cite this

Shim, S., & Yoon, J. W. (2019). A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack. In B. B. Kang, & J. Jang (Eds.), Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers (pp. 185-196). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11402 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-17982-3_15

A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack. / Shim, Shinwoo; Yoon, Ji Won.
Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers. ed. / Brent ByungHoon Kang; JinSoo Jang. Springer Verlag, 2019. p. 185-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11402 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shim, S & Yoon, JW 2019, A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack. in BB Kang & J Jang (eds), Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11402 LNCS, Springer Verlag, pp. 185-196, 19th World International Conference on Information Security and Application, WISA 2018, Jeju Island, Korea, Republic of, 18/8/23. https://doi.org/10.1007/978-3-030-17982-3_15

Shim S, Yoon JW. A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack. In Kang BB, Jang J, editors, Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers. Springer Verlag. 2019. p. 185-196. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-17982-3_15

Shim, Shinwoo ; Yoon, Ji Won. / A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack. Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers. editor / Brent ByungHoon Kang ; JinSoo Jang. Springer Verlag, 2019. pp. 185-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{bdafd4b067414e78badad45e257ae29a,

title = "A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack",

abstract = "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.",

keywords = "Bayesian network, Cyber warfare, Mission impact assessment",

author = "Shinwoo Shim and Yoon, {Ji Won}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 19th World International Conference on Information Security and Application, WISA 2018 ; Conference date: 23-08-2018 Through 25-08-2018",

year = "2019",

doi = "10.1007/978-3-030-17982-3_15",

language = "English",

isbn = "9783030179816",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "185--196",

editor = "Kang, {Brent ByungHoon} and JinSoo Jang",

booktitle = "Information Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers",

}

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

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 -

A new bayesian approach to exploring damaged assets by monitoring mission failures caused by undetected attack

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this