A probabilistic approach to estimate the damage propagation of cyber attacks

Young Gab Kim, Taek Lee, Hoh Peter In, Yoon Jung Chung, In Jung Kim, Doo Kwon Baik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

With rapid development in the Internet technology, business management in an organization becomes dependent on network dependency and cohesiveness in a critical information and communications infrastructure. However, the occurrence of cyber attacks has increased, targeted against vulnerable resources in information systems. Hence, in order to protect private information and computer resources, risk analysis and damage propagation need to be studied. However, the existing models present mechanisms for risk management, and these models can only be applied to specified threats such as a virus or a worm. Therefore, a probabilistic model for damage propagation based on Markov process is proposed, which can be applied to diverse threats in information systems. The proposed model enables us to predict the occurrence probability and occurrence frequency of each threat in the information systems.

Original languageEnglish
Title of host publicationInformation Security and Cryptology, ICISC 2005 - 8th International Conference, Revised Selected Papers
PublisherSpringer Verlag
Pages175-185
Number of pages11
ISBN (Print)3540333541, 9783540333548
DOIs
Publication statusPublished - 2006
Event8th International Conference on Information Security and Cryptology, ICISC 2005 - Seoul, Korea, Republic of
Duration: 2005 Dec 12005 Dec 2

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3935 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Information Security and Cryptology, ICISC 2005
Country/TerritoryKorea, Republic of
CitySeoul
Period05/12/105/12/2

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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