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Objective wording changes

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Noah L. Schrick 2022-04-20 10:15:12 -05:00
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.~lock.Schrick-Noah_MS-Defense-Presentation.ppt#
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,noah,NovaArchSys,17.04.2022 23:57,file:///home/noah/.config/libreoffice/4;

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Chapter1.tex
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@ -47,8 +47,8 @@ The objectives of this thesis are:
\begin{itemize}
\item{Extend the utility of RAGE to:}
\begin{enumerate}
\item{Reduce the complexity required for network model and exploit file creation}
\item{Expand the complexity of attack modeling}
\item{Reduce the difficulty required for network model and exploit file creation}
\item{Expand the expressiveness of attack modeling}
\item{Allow for the creation of a very large sized attack graph, assuming very large storage}
\item{Split Attack Graphs into subgraphs to simplify analysis of individual clusters}
\end{enumerate}

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Chapter6.tex
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\TUchapter{CONCLUSIONS AND FUTURE WORKS}
\TUsection{Conclusions}
This thesis presented various extensions to an attack graph generator, RAGE, to allow for a broader range of utilities. In order to reduce the complexity required for describing network models and exploits, Sections \ref{sec:compops} and \ref{sec:relops} presented the implementation of relational and compound operators. Both implementations simplify the amount of manual enumeration and manual specifications of asset qualities, and this simplifies precondition checks to singular lines. In addition, these implementations reduce the complexity required for synchronous firing exploit creations by avoiding the need for (for instance) time flags and enumeration of time all time instances. These expansions allow for more complex attack modeling, since broad sweeps and generic $<$ or $>$ checks can be performed.
This thesis presented various extensions to an attack graph generator, RAGE, to allow for a broader range of utilities. In order to reduce the difficulty required for describing network models and exploits, Sections \ref{sec:compops} and \ref{sec:relops} presented the implementation of relational and compound operators. Both implementations simplify the amount of manual enumeration and manual specifications of asset qualities, and this simplifies precondition checks to singular lines. In addition, these implementations reduce the difficulty required for synchronous firing exploit creations by avoiding the need for (for instance) time flags and enumeration of time all time instances. These expansions allow for more complex attack modeling, since broad sweeps and generic $<$ or $>$ checks can be performed due to the increased expressiveness.
The intermediate database storage feature presented in Section \ref{sec:db-stor} allows for the generation of very large attack or compliance graphs without concern of absolute memory consumption, assuming very large storage solutions are in place.