Time Independent Security Analysis for Dynamic Networks using Graphical Security Models

Simon Enoch Yusuf, Jin Bum Hong, Dong Seong Kim

Research output: Chapter in Book/Conference paperConference paper

1 Citation (Scopus)

Abstract

It is technically challenging to conduct a security analysis of a dynamic network, due to the lack of methods and techniques to capture different security postures as the network changes. Graphical Security Models (e.g., Attack Graph) are used to assess the security of network systems, but it typically captures a snapshot of a network state to carry out the security analysis. To address this issue, we propose a new Graphical Security Model named Time-independent Hierarchical Attack Representation Model (Ti-HARM) that captures security of multiple network states by taking into account the time duration of each network state and the visibility of network components (e.g., hosts, edges) in each state. By incorporating the changes, we can analyse the security of dynamic networks taking into account all the threats appearing in different network states. Our experimental results show that the Ti-HARM can effectively capture and assess the security of dynamic networks which were not possible using existing graphical security models.
Original languageEnglish
Title of host publication2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages588-595
Number of pages8
ISBN (Print)9781538643877
DOIs
Publication statusPublished - 2018
Event17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications / 12th IEEE International Conference On Big Data Science And Engineering, TrustCom/BigDataSE 2018 - New York, United States
Duration: 1 Aug 20183 Aug 2018

Conference

Conference17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications / 12th IEEE International Conference On Big Data Science And Engineering, TrustCom/BigDataSE 2018
CountryUnited States
CityNew York
Period1/08/183/08/18

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Yusuf, S. E., Hong, J. B., & Kim, D. S. (2018). Time Independent Security Analysis for Dynamic Networks using Graphical Security Models. In 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) (pp. 588-595). United States: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/TrustCom/BigDataSE.2018.00089
Yusuf, Simon Enoch ; Hong, Jin Bum ; Kim, Dong Seong. / Time Independent Security Analysis for Dynamic Networks using Graphical Security Models. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). United States : IEEE, Institute of Electrical and Electronics Engineers, 2018. pp. 588-595
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Yusuf, SE, Hong, JB & Kim, DS 2018, Time Independent Security Analysis for Dynamic Networks using Graphical Security Models. in 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 588-595, 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications / 12th IEEE International Conference On Big Data Science And Engineering, TrustCom/BigDataSE 2018, New York, United States, 1/08/18. https://doi.org/10.1109/TrustCom/BigDataSE.2018.00089

Time Independent Security Analysis for Dynamic Networks using Graphical Security Models. / Yusuf, Simon Enoch; Hong, Jin Bum; Kim, Dong Seong.

2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). United States : IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 588-595.

Research output: Chapter in Book/Conference paperConference paper

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N2 - It is technically challenging to conduct a security analysis of a dynamic network, due to the lack of methods and techniques to capture different security postures as the network changes. Graphical Security Models (e.g., Attack Graph) are used to assess the security of network systems, but it typically captures a snapshot of a network state to carry out the security analysis. To address this issue, we propose a new Graphical Security Model named Time-independent Hierarchical Attack Representation Model (Ti-HARM) that captures security of multiple network states by taking into account the time duration of each network state and the visibility of network components (e.g., hosts, edges) in each state. By incorporating the changes, we can analyse the security of dynamic networks taking into account all the threats appearing in different network states. Our experimental results show that the Ti-HARM can effectively capture and assess the security of dynamic networks which were not possible using existing graphical security models.

AB - It is technically challenging to conduct a security analysis of a dynamic network, due to the lack of methods and techniques to capture different security postures as the network changes. Graphical Security Models (e.g., Attack Graph) are used to assess the security of network systems, but it typically captures a snapshot of a network state to carry out the security analysis. To address this issue, we propose a new Graphical Security Model named Time-independent Hierarchical Attack Representation Model (Ti-HARM) that captures security of multiple network states by taking into account the time duration of each network state and the visibility of network components (e.g., hosts, edges) in each state. By incorporating the changes, we can analyse the security of dynamic networks taking into account all the threats appearing in different network states. Our experimental results show that the Ti-HARM can effectively capture and assess the security of dynamic networks which were not possible using existing graphical security models.

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Yusuf SE, Hong JB, Kim DS. Time Independent Security Analysis for Dynamic Networks using Graphical Security Models. In 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). United States: IEEE, Institute of Electrical and Electronics Engineers. 2018. p. 588-595 https://doi.org/10.1109/TrustCom/BigDataSE.2018.00089