skip to main content
10.1145/2809826.2809837acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
research-article
Public Access

Action Recommendation for Cyber Resilience

Published: 12 October 2015 Publication History

Abstract

This paper presents an unifying graph-based model for representing the infrastructure, behavior and missions of an enterprise. We describe how the model can be used to achieve resiliency against a wide class of failures and attacks. We introduce an algorithm for recommending resilience establishing actions based on dynamic updates to the models. Without loss of generality, we show the effectiveness of the algorithm for preserving latency based quality of service (QoS). Our models and the recommendation algorithms are implemented in a software framework that we seek to release as an open source framework for simulating resilient cyber systems.

References

[1]
A. Beck and M. Teboulle. A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM journal on imaging sciences, 2(1):183--202, 2009.
[2]
H. Chan, L. Akoglu, and H. Tong. Make it or break it: Manipulating robustness in large networks. SIAM, 2014.
[3]
R. Dewri, I. Ray, N. Poolsappasit, and D. Whitley. Optimal security hardening on attack tree models of networks: a cost-benefit analysis. International Journal of Information Security, 11(3):167--188, 2012.
[4]
Y. Hu, W. Wang, X. Gong, X. Que, and S. Cheng. On reliability-optimized controller placement for software-defined networks. Communications, China, 2014.
[5]
I. Linkov, D. A. Eisenberg, K. Plourde, T. P. Seager, J. Allen, and A. Kott. Resilience metrics for cyber systems. Environment Systems and Decisions, 33(4):471--476, 2013.
[6]
H. Okhravi, J. Riordan, and K. Carter. Quantitative evaluation of dynamic platform techniques as a defensive mechanism. In Research in Attacks, Intrusions and Defenses. Springer, 2014.
[7]
W. Peng, F. Li, C.-T. Huang, and X. Zou. A moving-target defense strategy for cloud-based services with heterogeneous and dynamic attack surfaces. In Communications (ICC), 2014 IEEE International Conference on. IEEE, 2014.
[8]
P. Ramuhalli, M. Halappanavar, J. Coble, and M. Dixit. Towards a theory of autonomous reconstitution of compromised cyber-systems. In Technologies for Homeland Security (HST), 2013 IEEE International Conference on. IEEE, 2013.
[9]
J. Xu, P. Guo, M. Zhao, R. F. Erbacher, M. Zhu, and P. Liu. Comparing different moving target defense techniques. In Proceedings of the First ACM Workshop on Moving Target Defense, pages 97--107. ACM, 2014.

Cited By

View all

Index Terms

  1. Action Recommendation for Cyber Resilience

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    SafeConfig '15: Proceedings of the 2015 Workshop on Automated Decision Making for Active Cyber Defense
    October 2015
    112 pages
    ISBN:9781450338219
    DOI:10.1145/2809826
    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]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 12 October 2015

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. cyber resilience
    2. cyber security
    3. recommendation engine

    Qualifiers

    • Research-article

    Funding Sources

    • Pacific Northwest National Laboratory

    Conference

    CCS'15
    Sponsor:

    Acceptance Rates

    SafeConfig '15 Paper Acceptance Rate 8 of 27 submissions, 30%;
    Overall Acceptance Rate 22 of 61 submissions, 36%

    Upcoming Conference

    CCS '25

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)81
    • Downloads (Last 6 weeks)9
    Reflects downloads up to 27 Dec 2024

    Other Metrics

    Citations

    Cited By

    View all

    View Options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Login options

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media