A monte carlo graph search algorithm with ant colony optimization for optimal attack path analysis

Hui Xie*, Kun Lv, Changzhen Hu, Chong Sun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

An optimal attack path is essential for an attacker. With an optimal attack path, the attacker can not only successfully carry out attacks, but also save time, energy and money. This article proposes a Monte Carlo Graph Search algorithm with Ant Colony Optimization(ACO-MCGS) to calculate optimal attack paths in target network. ACO-MCGS can get comprehensive results quickly and avoid the problem of path loss. ACO-MCGS has two steps to calculate optimal attack paths: Selection and backpropagation. A weight vector containing host priority, CVSS risk value , host link number is proposed for every host in the target network. The weight vector is applied to improved Ant Colony Optimization algorithm to calculate the evaluation value of every attack path, which is used to screen the optimal attack paths for the first round. The weight vector is also used to calculate the total CVSS value and the average CVSS value of every attack path. Results of our experiment demonstrate the capabilities of the proposed algorithm to generate optimal attack paths in one single run. The results obtained by ACO-MCGS show good performance and are compared with Ant Colony Optimization Algorithm (ACO).

Original languageEnglish
Title of host publicationICCCN 2018 - 27th International Conference on Computer Communications and Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538651568
DOIs
Publication statusPublished - 9 Oct 2018
Event27th International Conference on Computer Communications and Networks, ICCCN 2018 - Hangzhou City, Zhejiang Province, China
Duration: 30 Jul 20182 Aug 2018

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
Volume2018-July
ISSN (Print)1095-2055

Conference

Conference27th International Conference on Computer Communications and Networks, ICCCN 2018
Country/TerritoryChina
CityHangzhou City, Zhejiang Province
Period30/07/182/08/18

Keywords

  • Ant Colony Optimization
  • Dynamic programming
  • Monte Carlo Graph Search algorithm with Ant Colony Optimization
  • Network security
  • Optimal attack path

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Xie, H., Lv, K., Hu, C., & Sun, C. (2018). A monte carlo graph search algorithm with ant colony optimization for optimal attack path analysis. In ICCCN 2018 - 27th International Conference on Computer Communications and Networks Article 8487462 (Proceedings - International Conference on Computer Communications and Networks, ICCCN; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCN.2018.8487462