research-article

Techniques for attack graph visualization and interaction

Authors:

Zach Harbort,

G. Louthan,

J. HaleAuthors Info & Claims

CSIIRW '11: Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research

Article No.: 74, Page 1

https://doi.org/10.1145/2179298.2179383

Published: 12 October 2011 Publication History

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Abstract

Attack graphs provide a comprehensive overview of attack vectors. Unfortunately, their complexity dramatically increases as the number of hosts in a network grows. For realistic networks, the human eye cannot discern the state of a network without tracing individual attack paths. In order to combat this complexity, we discuss and implement mitigation techniques and the use of collaborative multi-touch environments for an intuitive, natural approach to visual analytics.

References

[1]

F. Chen, D. Liu, Y. Zhang, and J. Su. A scalable approach to analyzing network security using compact attack graphs. Journal of Networks, 5(5):543--550, 2010.

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[2]

S. Noel and S. Jajodia. Managing attack graph complexity through visual hierarchical aggregation. In Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security, pages 109--118. ACM, 2004.

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[3]

L. Williams, R. Lippmann, and K. Ingols. An interactive attack graph cascade and reachability display. VizSEC 2007, pages 221--236, 2008.

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Jang MKim DSeo DJu YRyu SYoon H(2020)An intelligent recommendation algorithm for red team strategy in edge computing powered massive Cyber Defense ExerciseComputer Communications10.1016/j.comcom.2020.10.008Online publication date: Nov-2020
https://doi.org/10.1016/j.comcom.2020.10.008
(2016)Network forensicsJournal of Network and Computer Applications10.1016/j.jnca.2016.03.00566:C(214-235)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.03.005
Chandran RYan W(2014)Attack Graph Analysis for Network Anti-ForensicsInternational Journal of Digital Crime and Forensics10.4018/ijdcf.20140101036:1(28-50)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.4018/ijdcf.2014010103

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Published In

CSIIRW '11: Proceedings of the Seventh Annual Workshop on Cyber Security and Information Intelligence Research

October 2011

18 pages

ISBN:9781450309455

DOI:10.1145/2179298

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 October 2011

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Research-article

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CSIIRW '11

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Eurosis
University of Tennessee

CSIIRW '11: Cyber Security and Information Intelligence Research Workshop

October 12 - 14, 2011

Tennessee, Oak Ridge, USA

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Cited By

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Jang MKim DSeo DJu YRyu SYoon H(2020)An intelligent recommendation algorithm for red team strategy in edge computing powered massive Cyber Defense ExerciseComputer Communications10.1016/j.comcom.2020.10.008Online publication date: Nov-2020
https://doi.org/10.1016/j.comcom.2020.10.008
(2016)Network forensicsJournal of Network and Computer Applications10.1016/j.jnca.2016.03.00566:C(214-235)Online publication date: 1-May-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.03.005
Chandran RYan W(2014)Attack Graph Analysis for Network Anti-ForensicsInternational Journal of Digital Crime and Forensics10.4018/ijdcf.20140101036:1(28-50)Online publication date: 1-Jan-2014
https://dl.acm.org/doi/10.4018/ijdcf.2014010103

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Recommendations

Attack Intent Analysis Method Based on Attack Path Graph

Improving Attack Graph Visualization through Data Reduction and Attack Grouping

Attack Intent Analysis Method Based on Attack Path Graph