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A New Bayesian Approach to Exploring Damaged Assets by Monitoring Mission Failures Caused by Undetected Attack

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Information Security Applications (WISA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11402))

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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.

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Author information

Authors and Affiliations

  1. Graduate School of Information Security, Korea University, Seoul, Republic of Korea

    Shinwoo Shim & Ji Won Yoon

  2. Cyber Warfare R&D Lab, LIG Nex1 Co., Seongnam, Republic of Korea

    Shinwoo Shim

Authors
  1. Shinwoo Shim
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  2. Ji Won Yoon
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Corresponding author

Correspondence to Ji Won Yoon .

Editor information

Editors and Affiliations

  1. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Brent ByungHoon Kang

  2. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    JinSoo Jang

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Shim, S., Yoon, J.W. (2019). A New Bayesian Approach to Exploring Damaged Assets by Monitoring Mission Failures Caused by Undetected Attack. In: Kang, B., Jang, J. (eds) Information Security Applications. WISA 2018. Lecture Notes in Computer Science(), vol 11402. Springer, Cham. https://doi.org/10.1007/978-3-030-17982-3_15

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  • DOI: https://doi.org/10.1007/978-3-030-17982-3_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17981-6

  • Online ISBN: 978-3-030-17982-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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