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Visualizing attack graphs, reachability, and trust relationships with NAVIGATOR

Published: 14 September 2010 Publication History

Abstract

A new tool named NAVIGATOR (Network Asset VIsualization: Graphs, ATtacks, Operational Recommendations) adds significant capabilities to earlier work in attack graph visualization. Using NAVIGATOR, users can visualize the effect of server-side, client-side, credential-based, and trust-based attacks. By varying the attacker model, NAVIGATOR can show the current state of the network as well as hypothetical future situations, allowing for advance planning. Furthermore, NAVIGATOR explicitly shows network topology, infrastructure devices, and host-level data while still conveying situational awareness of the network as a whole. This tool is implemented in Java and uses an existing C++ engine for reachability and attack graph calculations.

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      cover image ACM Other conferences
      VizSec '10: Proceedings of the Seventh International Symposium on Visualization for Cyber Security
      September 2010
      123 pages
      ISBN:9781450300131
      DOI:10.1145/1850795
      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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      New York, NY, United States

      Publication History

      Published: 14 September 2010

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      Author Tags

      1. attack graph
      2. attack path
      3. client-side vulnerability
      4. treemap
      5. visualization

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      VizSec '10 Paper Acceptance Rate 12 of 27 submissions, 44%;
      Overall Acceptance Rate 39 of 111 submissions, 35%

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      • (2023)Automated Security Assessments of Amazon Web Services EnvironmentsACM Transactions on Privacy and Security10.1145/357090326:2(1-31)Online publication date: 13-Mar-2023
      • (2023)FASHION: Functional and Attack Graph Secured HybrId Optimization of Virtualized NetworksIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2022.319884320:4(3093-3109)Online publication date: 1-Jul-2023
      • (2023)Cyberattack Graph Modeling for Visual AnalyticsIEEE Access10.1109/ACCESS.2023.330464011(86910-86944)Online publication date: 2023
      • (2023)Attack graph analysisComputers and Security10.1016/j.cose.2022.103081126:COnline publication date: 1-Mar-2023
      • (2022)A Layered Reference Model for Penetration Testing with Reinforcement Learning and Attack Graphs2022 IEEE 29th Annual Software Technology Conference (STC)10.1109/STC55697.2022.00015(41-50)Online publication date: Oct-2022
      • (2022)Toward Automated Security Analysis and Enforcement for Cloud Computing Using Graphical Models for SecurityIEEE Access10.1109/ACCESS.2022.319054510(75117-75134)Online publication date: 2022
      • (2022)A Multi-level Cyber-Security Reference Model in Support of Vulnerability AnalysisEnterprise Design, Operations, and Computing10.1007/978-3-031-17604-3_2(19-35)Online publication date: 28-Sep-2022
      • (2021)SAGE: Intrusion Alert-driven Attack Graph Extractor2021 IEEE Symposium on Visualization for Cyber Security (VizSec)10.1109/VizSec53666.2021.00009(36-41)Online publication date: Oct-2021
      • (2021)BUCEPHALUS: a BUsiness CEntric cybersecurity Platform for proActive anaLysis Using visual analyticS2021 IEEE Symposium on Visualization for Cyber Security (VizSec)10.1109/VizSec53666.2021.00007(15-25)Online publication date: Oct-2021
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