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

Shinwoo Shim, Ji Won Yoon

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationInformation Security Applications - 19th International Conference, WISA 2018, Revised Selected Papers
EditorsBrent ByungHoon Kang, JinSoo Jang
PublisherSpringer Verlag
Pages185-196
Number of pages12
ISBN (Print)9783030179816
DOIs
Publication statusPublished - 2019
Event19th World International Conference on Information Security and Application, WISA 2018 - Jeju Island, Korea, Republic of
Duration: 2018 Aug 232018 Aug 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11402 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th World International Conference on Information Security and Application, WISA 2018
Country/TerritoryKorea, Republic of
CityJeju Island
Period18/8/2318/8/25

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
  • Computer Science(all)

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