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\citation{zhang_boosting_2017}
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\newlabel{CG-alter}{{1.2.2}{2}}
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\citation{cook_rage_2018}
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\TUchapter{INTRODUCTION}
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\TUsection{Introduction to Attack Graphs} \label{sec:Into}
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\TUsection{Introduction to Attack Graphs} \label{sec:Intro}
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Cybersecurity has been at the forefront of computing for decades, and vulnerability analysis modeling has been utilized to mitigate threats to aid in this effort. One such modeling approach
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is to represent a system or a set of systems through graphical means, and encode information into the nodes and edges of the graph. Even as early as the late 1990s,
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experts have composed various graphical models to map devices and vulnerabilities through attack trees, and this work can be seen through the works published by the authors of \cite{phillips_graph-based_1998}.
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\end{table}
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\TUsubsection{Performance Expectations}
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Due to the amount of communication between nodes to distribute the necessary data through all stages of the tasking pipeline, this approach is not expected to outperform the serial approach in all cases. This tasking approach was specifically designed to reduce the computation time when the generation of each individual state increases in time. This approach does not offer any guarantees of processing through the frontier at an increased rate; it's main objective is to distribute the workload of individual state generation. As discussed in Section \ref{sec:Intro}, the amount of entries in the National Vulnerability database and any custom vulnerability testing to ensure adequate examination of all assets in the network sums to large number of exploits in the exploit list. Likewise for compliance graphs and compliance examinations, Section \ref{sec:CG-diff} mentioned the number of compliance checks for SOX, HIPAA, GDPR, PCI DSS, and/or any other regulatory compliance also sums to a large number of exploits in the exploit list. Since the generation of each state is largely dependent on the number of exploits present in the exploit list, this approach is best-suited for when the exploit list grows in size.
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Due to the amount of communication between nodes to distribute the necessary data through all stages of the tasking pipeline, this approach is not expected to outperform the serial approach in all cases. This tasking approach was specifically designed to reduce the computation time when the generation of each individual state increases in time. This approach does not offer any guarantees of processing through the frontier at an increased rate; it's main objective is to distribute the workload of individual state generation. As discussed in Section \ref{sec:Intro}, the amount of entries in the National Vulnerability database and any custom vulnerability testing to ensure adequate examination of all assets in the network sums to large number of exploits in the exploit list. Likewise for compliance graphs and compliance examinations, Section \ref{sec:CG-diff} discussed that the number of compliance checks for SOX, HIPAA, GDPR, PCI DSS, and/or any other regulatory compliance also sums to a large number of exploits in the exploit list. Since the generation of each state is largely dependent on the number of exploits present in the exploit list, this approach is best-suited for when the exploit list grows in size.
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\TUsubsection{Results}
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Communication cost of asynchronous send for T4 and T5 is less than the time requirement of a database storage by root.
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\bibdata{Bibliography}
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\bibcite{noauthor_boost_nodate}{1}
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\bibcite{noauthor_overview_nodate}{2}
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\bibcite{ainsworth_graph_2016}{3}
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\bibcite{allman_complying_2006}{4}
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\bibcite{arifuzzaman_fast_2015}{5}
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\bibcite{balaji_graph_2016}{6}
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\bibcite{phillips_graph-based_1998}{1}
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\bibcite{schneier_modeling_1999}{2}
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\bibcite{ou_scalable_2006}{3}
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\bibcite{sheyner_automated_2002}{4}
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\bibcite{zhang_boosting_2017}{5}
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\bibcite{j_hale_compliance_nodate}{6}
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\bibcite{baloyi_guidelines_2019}{7}
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\bibcite{berry_graph_2007}{8}
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\bibcite{allman_complying_2006}{8}
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\bibcite{cook_rage_2018}{9}
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\bibcite{cook_scalable_2016}{10}
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\bibcite{berry_graph_2007}{10}
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\bibcite{CVE-2019-10747}{11}
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\bibcite{dai_fpgp_2016}{12}
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\bibcite{j_hale_compliance_nodate}{13}
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\bibcite{7087377}{14}
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\bibcite{li_combining_2019}{15}
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\bibcite{li_concurrency_2019}{16}
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\bibcite{9150145}{17}
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\bibcite{liakos_memory-optimized_2016}{18}
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\bibcite{louthan_hybrid_2011}{19}
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\bibcite{ou_scalable_2006}{20}
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\bibcite{phillips_graph-based_1998}{21}
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\bibcite{schneier_modeling_1999}{22}
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\bibcite{sheyner_automated_2002}{23}
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\bibcite{yao_efficient_2018}{24}
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\bibcite{yu_construction_2018}{25}
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\bibcite{zhang_boosting_2017}{26}
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\bibstyle{plain}
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\bibcite{ainsworth_graph_2016}{11}
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\bibcite{yao_efficient_2018}{12}
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\bibcite{dai_fpgp_2016}{13}
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\bibcite{arifuzzaman_fast_2015}{14}
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\bibcite{yu_construction_2018}{15}
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\bibcite{liakos_memory-optimized_2016}{16}
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\bibcite{balaji_graph_2016}{17}
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\bibcite{noauthor_overview_nodate}{18}
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\bibcite{noauthor_boost_nodate}{19}
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\bibcite{cook_scalable_2016}{20}
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\bibcite{li_concurrency_2019}{21}
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\bibcite{9150145}{22}
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\bibcite{7087377}{23}
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\bibcite{li_combining_2019}{24}
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\bibcite{CVE-2019-10747}{25}
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\bibcite{louthan_hybrid_2011}{26}
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\bibstyle{ieeetr}
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@ -1,158 +1,133 @@
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\begin{thebibliography}{10}
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\bibitem{noauthor_boost_nodate}
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The {Boost} {Graph} {Library} - 1.75.0.
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\bibitem{phillips_graph-based_1998}
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C.~Phillips and L.~P. Swiler, ``A graph-based system for network-vulnerability
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analysis,'' {\em Proceedings New Security Paradigms Workshop}, vol.~Part
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F1292, pp.~71--79, 1998.
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\bibitem{noauthor_overview_nodate}
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||||
An {Overview} of the {Parallel} {Boost} {Graph} {Library} - 1.75.0.
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||||
\bibitem{schneier_modeling_1999}
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B.~Schneier, ``Modeling {Security} {Threats},'' 1999.
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||||
\newblock Publication Title: Dr. Dobb's Journal.
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||||
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\bibitem{ainsworth_graph_2016}
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Sam Ainsworth and Timothy~M. Jones.
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\newblock Graph prefetching using data structure knowledge.
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\newblock {\em Proceedings of the International Conference on Supercomputing},
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01-03-June, 2016.
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\bibitem{ou_scalable_2006}
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||||
X.~Ou, W.~F. Boyer, and M.~A. Mcqueen, ``A {Scalable} {Approach} to {Attack}
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{Graph} {Generation},'' pp.~336--345, 2006.
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\bibitem{allman_complying_2006}
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Eric Allman.
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\newblock Complying with {Compliance}: {Blowing} it off is not an option.
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\newblock {\em ACM Queue}, 4(7), 2006.
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||||
\bibitem{sheyner_automated_2002}
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||||
O.~Sheyner, J.~Haines, S.~Jha, R.~Lippmann, and J.~Wing, ``Automated
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||||
{Generation} and {Analysis} of {Attack} {Graphs},'' {\em Proceeding of 2002
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IEEE Symposium on Security and Privacy}, pp.~254--265, 2002.
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\bibitem{arifuzzaman_fast_2015}
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Shaikh Arifuzzaman and Maleq Khan.
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\newblock Fast parallel conversion of edge list to adjacency list for
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large-scale graphs.
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||||
\newblock In {\em {HPC} '15: {Proceedings} of the {Symposium} on {High}
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||||
{Performance} {Computing}}, pages 17--24, April 2015.
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||||
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\bibitem{balaji_graph_2016}
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Janani Balaji and Rajshekhar Sunderraman.
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||||
\newblock Graph {Topology} {Abstraction} for {Distributed} {Path} {Queries}.
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||||
\newblock In {\em {HPGP} '16: {Proceedings} of the {ACM} {Workshop} on {High}
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||||
{Performance} {Graph} {Processing}}, pages 27--34, May 2016.
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||||
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\bibitem{baloyi_guidelines_2019}
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||||
Ntsako Baloyi and Paula Kotzé.
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||||
\newblock Guidelines for {Data} {Privacy} {Compliance}: {A} {Focus} on
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{Cyberphysical} {Systems} and {Internet} of {Things}.
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||||
\newblock In {\em {SAICSIT} '19: {Proceedings} of the {South} {African}
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||||
{Institute} of {Computer} {Scientists} and {Information} {Technologists}
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2019}, Skukuza South Africa, 2019. Association for Computing Machinery.
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\bibitem{berry_graph_2007}
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Jonathan Berry and Bruce Hendrickson.
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\newblock Graph {Analysis} with {High} {Performance} {Computing}.
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\newblock {\em Computing in Science and Engineering}, 2007.
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||||
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||||
\bibitem{cook_rage_2018}
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Kyle Cook.
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\newblock {\em {RAGE}: {The} {Rage} {Attack} {Graph} {Engine}}.
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\newblock PhD thesis, 2018.
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\bibitem{cook_scalable_2016}
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Kyle Cook, Thomas Shaw, John Hale, and Peter Hawrylak.
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\newblock Scalable attack graph generation.
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\newblock {\em Proceedings of the 11th Annual Cyber and Information Security
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Research Conference, CISRC 2016}, 2016.
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||||
\bibitem{CVE-2019-10747}
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{set-value is vulnerable to Prototype Pollution in versions lower than 3.0.1.
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The function mixin-deep could be tricked into adding or modifying properties
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of Object.prototype using any of the constructor, prototype and $\_$proto$\_$
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payloads.}
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\newblock National Vulnerability Database, August 2019.
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\bibitem{dai_fpgp_2016}
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||||
Guohao Dai, Yuze Chi, Yu~Wang, and Huazhong Yang.
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||||
\newblock {FPGP}: {Graph} processing framework on {FPGA}: {A} case study of
|
||||
breadth-first search.
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||||
\newblock {\em FPGA 2016 - Proceedings of the 2016 ACM/SIGDA International
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||||
Symposium on Field-Programmable Gate Arrays}, pages 105--110, 2016.
|
||||
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||||
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||||
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||||
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J.~Balaji and R.~Sunderraman, ``Graph {Topology} {Abstraction} for
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||||
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||||
\bibitem{noauthor_overview_nodate}
|
||||
``An {Overview} of the {Parallel} {Boost} {Graph} {Library} - 1.75.0.''
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||||
|
||||
\bibitem{noauthor_boost_nodate}
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
M.~Li, P.~Hawrylak, and J.~Hale, ``Concurrency {Strategies} for {Attack}
|
||||
{Graph} {Generation},'' {\em Proceedings - 2019 2nd International Conference
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||||
on Data Intelligence and Security, ICDIS 2019}, pp.~174--179, 2019.
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||||
|
||||
\bibitem{9150145}
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||||
M.~Li, P.~J. Hawrylak, and J.~Hale, ``Implementing an attack graph generator in
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||||
cuda,'' in {\em 2020 IEEE International Parallel and Distributed Processing
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||||
Symposium Workshops (IPDPSW)}, pp.~730--738, 2020.
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||||
|
||||
\bibitem{7087377}
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||||
K.~Kaynar and F.~Sivrikaya, ``Distributed attack graph generation,'' {\em IEEE
|
||||
Transactions on Dependable and Secure Computing}, vol.~13, no.~5,
|
||||
pp.~519--532, 2016.
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||||
|
||||
\bibitem{li_combining_2019}
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||||
M.~Li, P.~Hawrylak, and J.~Hale, ``Combining {OpenCL} and {MPI} to support
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||||
heterogeneous computing on a cluster,'' {\em ACM International Conference
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||||
Proceeding Series}, 2019.
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||||
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||||
\bibitem{CVE-2019-10747}
|
||||
``{set-value is vulnerable to Prototype Pollution in versions lower than 3.0.1.
|
||||
The function mixin-deep could be tricked into adding or modifying properties
|
||||
of Object.prototype using any of the constructor, prototype and $\_$proto$\_$
|
||||
payloads.}.'' National Vulnerability Database, Aug. 2019.
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||||
|
||||
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||||
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||||
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||||
G.~Louthan, {\em Hybrid {Attack} {Graphs} for {Modeling} {Cyber}-{Physical}
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||||
{Systems}}.
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||||
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||||
|
||||
\bibitem{ou_scalable_2006}
|
||||
Xinming Ou, Wayne~F Boyer, and Miles~A Mcqueen.
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||||
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||||
\newblock pages 336--345, 2006.
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||||
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pages 254--265, 2002.
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||||
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||||
management.
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||||
Proceedings, PACT}, 2018.
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||||
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||||
{Scalable} {Distributed} {Message} {System}.
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||||
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||||
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||||
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||||
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||||
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|
||||
memory cube: {A} case for breadth first search.
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||||
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|
||||
Symposium on Field-Programmable Gate Arrays}, pages 207--216, 2017.
|
||||
|
||||
\end{thebibliography}
|
||||
|
||||
@ -8,55 +8,53 @@ A level-1 auxiliary file: Chapter4.aux
|
||||
A level-1 auxiliary file: Chapter5.aux
|
||||
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|
||||
A level-1 auxiliary file: Chapter7.aux
|
||||
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|
||||
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|
||||
A level-1 auxiliary file: Appendices.aux
|
||||
Database file #1: Bibliography.bib
|
||||
Warning--entry type for "j_hale_compliance_nodate" isn't style-file defined
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
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This is pdfTeX, Version 3.141592653-2.6-1.40.23 (TeX Live 2021/Arch Linux) (preloaded format=pdflatex 2022.2.14) 20 MAR 2022 13:08
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||||
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||||
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||||
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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||||
% APPENDICES AS NECESSARY
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||||
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||||
@ -56,42 +56,42 @@
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||||
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||||
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||||
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|
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|
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|
||||
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|
||||
\contentsline {subsection}{\numberline {6.1.1}\it Test Information}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.1.2}\it Results}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.1.3}\it Analysis}{35}{}%
|
||||
\contentsline {section}{\numberline {6.2}\bf Large Networks}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.2.1}\it Test Information}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.2.2}\it Results}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.2.3}\it Analysis}{35}{}%
|
||||
\contentsline {section}{\numberline {6.3}\bf Large Exploit Lists}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.3.1}\it Test Information}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.3.2}\it Results}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.3.3}\it Analysis}{35}{}%
|
||||
\contentsline {section}{\numberline {6.4}\bf Distributed Hash Tables}{35}{}%
|
||||
\contentsline {subsection}{\numberline {6.4.1}\it Test Information}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.4.2}\it Results}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.4.3}\it Analysis}{36}{}%
|
||||
\contentsline {chapter}{\numberline {CHAPTER 7: }{\bf \uppercase {CONCLUSIONS AND FUTURE WORKS}}}{37}{}%
|
||||
\contentsline {section}{\numberline {7.1}\bf Future Work}{37}{}%
|
||||
\contentsline {subsubsection}{Root Node}{35}{}%
|
||||
\contentsline {subsubsection}{Database Node}{35}{}%
|
||||
\contentsline {subsection}{\numberline {5.4.3}\it Performance Expectations}{35}{}%
|
||||
\contentsline {chapter}{\numberline {CHAPTER 6: }{\bf \uppercase {PERFORMANCE ANALYSIS}}}{36}{}%
|
||||
\contentsline {section}{\numberline {6.1}\bf Small Networks}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.1.1}\it Test Information}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.1.2}\it Results}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.1.3}\it Analysis}{36}{}%
|
||||
\contentsline {section}{\numberline {6.2}\bf Large Networks}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.2.1}\it Test Information}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.2.2}\it Results}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.2.3}\it Analysis}{36}{}%
|
||||
\contentsline {section}{\numberline {6.3}\bf Large Exploit Lists}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.3.1}\it Test Information}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.3.2}\it Results}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.3.3}\it Analysis}{36}{}%
|
||||
\contentsline {section}{\numberline {6.4}\bf Distributed Hash Tables}{36}{}%
|
||||
\contentsline {subsection}{\numberline {6.4.1}\it Test Information}{37}{}%
|
||||
\contentsline {subsection}{\numberline {6.4.2}\it Results}{37}{}%
|
||||
\contentsline {subsection}{\numberline {6.4.3}\it Analysis}{37}{}%
|
||||
\contentsline {chapter}{\numberline {CHAPTER 7: }{\bf \uppercase {CONCLUSIONS AND FUTURE WORKS}}}{38}{}%
|
||||
\contentsline {section}{\numberline {7.1}\bf Future Work}{38}{}%
|
||||
{\hfill \ }
|
||||
\contentsline {section}{\hspace {-\parindent }NOMENCLATURE}{38}{}%
|
||||
\contentsline {section}{\hspace {-\parindent }NOMENCLATURE}{39}{}%
|
||||
\addvspace {10pt}
|
||||
\contentsline {section}{\hspace {-\parindent }BIBLIOGRAPHY}{38}{}%
|
||||
\contentsline {section}{\hspace {-\parindent }BIBLIOGRAPHY}{39}{}%
|
||||
{\hfill \ }
|
||||
\contentsline {section}{\hspace {-\parindent }APPENDIX A:\ \ {\bf \uppercase {THE FIRST APPENDIX}} }{41}{}%
|
||||
\contentsline {section}{\hspace {-\parindent }APPENDIX B:\ \ {\bf \uppercase {THE SECOND APPENDIX}} }{42}{}%
|
||||
\contentsline {section}{\numberline {B.1}\bf A Heading in an Appendix}{42}{}%
|
||||
\contentsline {subsection}{\numberline {B.1.1}\it A Subheading in an Appendix}{42}{}%
|
||||
\contentsline {subsubsection}{A Sub-subsection in an Appendix}{42}{}%
|
||||
\contentsline {section}{\hspace {-\parindent }APPENDIX A:\ \ {\bf \uppercase {THE FIRST APPENDIX}} }{42}{}%
|
||||
\contentsline {section}{\hspace {-\parindent }APPENDIX B:\ \ {\bf \uppercase {THE SECOND APPENDIX}} }{43}{}%
|
||||
\contentsline {section}{\numberline {B.1}\bf A Heading in an Appendix}{43}{}%
|
||||
\contentsline {subsection}{\numberline {B.1.1}\it A Subheading in an Appendix}{43}{}%
|
||||
\contentsline {subsubsection}{A Sub-subsection in an Appendix}{43}{}%
|
||||
|
||||
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Reference in New Issue
Block a user