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@ -210,3 +210,29 @@ pages = {},
title = {Analysis of Attack Graph Representations for Ranking Vulnerability Fixes},
doi = {10.29007/2c1q}
}
@misc{DMCA,
title = {H.R.2281 - {Digital {Millennium} {Copyright} {Act}}},
note = {Pub. L. No. 105-304. 1998 [Online]. Available: https://www.govinfo.gov/content/pkg/PLAW-105publ304/html/PLAW-105publ304.htm},
}
@inproceedings{Piracy,
author={Kim, Yesol and Moon, Jeongoh and Cho, Seong Je and Park, Minkyu and Han, Sangchul},
booktitle={2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing},
title={Efficient Identification of Windows Executable Programs to Prevent Software Piracy},
year={2014},
volume={},
number={},
pages={236-240},
doi={10.1109/IMIS.2014.29}
}
@inproceedings{Android_Piracy,
author={Kumari, Neha and Chen, Min},
booktitle={2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR)},
title={Malware and Piracy Detection in Android Applications},
year={2022},
volume={},
number={},
pages={306-311},
doi={10.1109/MIPR54900.2022.00061}}

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\bibdata{Bibliography}
\bibcite{phillips_graph-based_1998}{1}
\bibcite{schneier_modeling_1999}{2}
\bibcite{ou_scalable_2006}{3}
\bibcite{CPSIOT}{4}
\bibcite{ming_jo}{5}
\bibcite{10.1145/3105760}{6}
\bibcite{8290918}{7}
\bibcite{centrality_based}{8}
\bibcite{j_hale_compliance_nodate}{9}
\bibcite{baloyi_guidelines_2019}{10}
\bibcite{allman_complying_2006}{11}
\bibcite{sheyner_automated_2002}{12}
\bibcite{zhang_boosting_2017}{13}
\bibcite{Monotonicity}{14}
\bibcite{TVA}{15}
\bibcite{louthan_hybrid_2011}{16}
\bibcite{cook_rage_2018}{17}
\bibcite{nichols_2018}{18}
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\begin{thebibliography}{10}
\bibitem{phillips_graph-based_1998}
C.~Phillips and L.~P. Swiler, ``A graph-based system for network-vulnerability
analysis,'' {\em Proceedings New Security Paradigms Workshop}, vol.~Part
F1292, pp.~71--79, 1998.
\newblock doi: 10.1145/310889.310919.
\bibitem{schneier_modeling_1999}
B.~Schneier, ``Modeling {Security} {Threats},'' {\em Dr. Dobb's Journal}, 1999.
\newblock vol. 24, no.12.
\bibitem{ou_scalable_2006}
X.~Ou, W.~F. Boyer, and M.~A. Mcqueen, ``A {Scalable} {Approach} to {Attack}
{Graph} {Generation},'' {\em CCS '06: Proceedings of the 13th ACM conference
on Computer and communications security}, pp.~336--345, 2006.
\bibitem{CPSIOT}
A.~T. Al~Ghazo, M.~Ibrahim, H.~Ren, and R.~Kumar, ``A2g2v: Automated attack
graph generator and visualizer,'' in {\em Proceedings of the 1st ACM MobiHoc
Workshop on Mobile IoT Sensing, Security, and Privacy}, Mobile IoT SSP'18,
(New York, NY, USA), Association for Computing Machinery, 2018.
\bibitem{ming_jo}
M.~Li, P.~Hawrylak, and J.~Hale, ``Strategies for practical hybrid attack graph
generation and analysis,'' {\em Digital Threats}, oct 2021.
\newblock Just Accepted.
\bibitem{10.1145/3105760}
L.~Mu\~{n}oz Gonz\'{a}lez, D.~Sgandurra, A.~Paudice, and E.~C. Lupu,
``Efficient attack graph analysis through approximate inference,'' {\em ACM
Trans. Priv. Secur.}, vol.~20, jul 2017.
\bibitem{8290918}
H.~Wang, Z.~Chen, J.~Zhao, X.~Di, and D.~Liu, ``A vulnerability assessment
method in industrial internet of things based on attack graph and maximum
flow,'' {\em IEEE Access}, vol.~6, pp.~8599--8609, 2018.
\bibitem{centrality_based}
T.~Gonda, T.~Pascal, R.~Puzis, G.~Shani, and B.~Shapira, ``Analysis of attack
graph representations for ranking vulnerability fixes,'' 09 2018.
\bibitem{j_hale_compliance_nodate}
{J. Hale}, P.~Hawrylak, and M.~Papa, ``Compliance {Method} for a
{Cyber}-{Physical} {System}.''
\newblock U.S. Patent Number 9,471,789, Oct. 18, 2016.
\bibitem{baloyi_guidelines_2019}
N.~Baloyi and P.~Kotzé, ``Guidelines for {Data} {Privacy} {Compliance}: {A}
{Focus} on {Cyberphysical} {Systems} and {Internet} of {Things},'' in {\em
{SAICSIT} '19: {Proceedings} of the {South} {African} {Institute} of
{Computer} {Scientists} and {Information} {Technologists} 2019}, (Skukuza
South Africa), Association for Computing Machinery, 2019.
\bibitem{allman_complying_2006}
E.~Allman, ``Complying with {Compliance}: {Blowing} it off is not an option.,''
{\em ACM Queue}, vol.~4, no.~7, 2006.
\bibitem{sheyner_automated_2002}
O.~Sheyner, J.~Haines, S.~Jha, R.~Lippmann, and J.~Wing, ``Automated
{Generation} and {Analysis} of {Attack} {Graphs},'' {\em Proceeding of 2002
IEEE Symposium on Security and Privacy}, pp.~254--265, 2002.
\bibitem{zhang_boosting_2017}
J.~Zhang, S.~Khoram, and J.~Li, ``Boosting the performance of {FPGA}-based
graph processor using hybrid memory cube: {A} case for breadth first
search,'' {\em FPGA 2017 - Proceedings of the 2017 ACM/SIGDA International
Symposium on Field-Programmable Gate Arrays}, pp.~207--216, 2017.
\bibitem{Monotonicity}
P.~Ammann, D.~Wijesekera, and S.~Kaushik, ``Scalable, graph-based network
vulnerability analysis,'' in {\em Proceedings of the 9th ACM Conference on
Computer and Communications Security}, CCS '02, (New York, NY, USA),
p.~217–224, Association for Computing Machinery, 2002.
\bibitem{TVA}
S.~Jajodia and S.~Noel, {\em Topological Vulnerability Analysis}, vol.~46,
pp.~139--154.
\newblock 09 2010.
\bibitem{louthan_hybrid_2011}
G.~Louthan, {\em Hybrid {Attack} {Graphs} for {Modeling} {Cyber}-{Physical}
{Systems}}.
\newblock PhD thesis, The {University} of {Tulsa}, 2011.
\bibitem{cook_rage_2018}
K.~Cook, {\em {RAGE}: {The} {Rage} {Attack} {Graph} {Engine}}.
\newblock PhD thesis, The {University} of {Tulsa}, 2018.
\bibitem{nichols_2018}
W.~M. Nichols, {\em {Hybrid} {Attack} {Graphs} for {Use} with a {Simulation} of
a {Cyber-Physical} {System}}.
\newblock PhD thesis, The {University} of {Tulsa}, 2018.
\end{thebibliography}

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@ -169,6 +169,7 @@ All data was collected on a 13 node cluster, with 12 nodes serving as dedicated
\end{itemize}
All nodes are connected with a 10Gbps Infiniband interconnect.
\subsubsection{Automobile Maintenance}
The example networks for testing the effectiveness of synchronous firing follow the compliance graph generation approach. These networks analyze two assets, both of which are identical 2006 Toyota Corolla cars with identical qualities. The generation examines both cars at their current states, and proceeds to advance in time by a pre-determined amount, up to a pre-determined limit. Each time increment updates each car by an identical amount of mileage. During the generation process, it is determined if a car is out of compliance either through mileage or time since its last maintenance in accordance with the Toyota Corolla Maintenance Schedule manual.
In addition, the tests employ the use of ``services", where if a car is out of compliance, it will go through a correction process and reset the mileage and time since last service. Each test varies in the number of services used. The 1 Service case only employs one service, and it is dedicated to brake pads. The 2-Service case employs two services, where the first service is dedicated to the brake pads, and the second is for exhaust pipes. This process extends to the 3-, 4-, 5-, and 6-Service cases.
@ -193,8 +194,29 @@ The compliance checks are as follows:
\item{Driveshaft boots: to be checked every 12,000 miles}
\end{itemize}
\subsubsection{DMCA Takedown}
A second example of synchronous firing is illustrated through a DMCA Takedown for a fictitious organization \cite{DMCA}. In this example, a DMCA Takedown is issued to an organization after a group of employees were found to be engaging in online piracy with torrenting software on company devices and using company resources. Detection and removal of illicit data, such as through means presented by the authors of \cite{Piracy} for Windows or \cite{Android_Piracy} for company-supplied Android mobile devices, can be incorporated into and represented by a compliance graph.
Only the subset of the organization's network which contains the illicit data is used for this example. The graph generation process walks through as a system administrator removes the torrenting software and the illicit data from the company devices. When removing torrenting software, the data associated with the torrenting program can be removed at the same time; an administrator does not need to remove the torrenting program and then separately remove the data. This example highlights the capability of synchronous firing by grouping the removal of software and data together, as opposed to traditional attack and compliance graphs requiring at least two separate steps to remove the software and data.
This experimental setup is as follows:
\begin{itemize}
\item{Employee A has torrenting software, and is actively uploading and downloading 3 programs.}
\item{Employee B has torrenting software, and is actively uploading and downloading 4 programs.}
\item{Employee C has torrenting software, and is actively uploading and downloading 7 programs.}
\item{If synchronous firing is not enabled, the administrator removes each illicit program one-by-one after the removal of the torrenting software.}
\item{If synchronous firing is enabled, the administrator removes the torrenting software and all programs off a single device simultaneously.}
\item{Graph visualization was not timed. Only the generation and database operation time was measured.}
\end{itemize}
The compliance checks are as follows:
\begin{itemize}
\item{Does an employee have torrenting software}
\item{Does an employee have illicit data}
\end{itemize}
\subsection{Results and Analysis}
\subsubsection{Results for the Theoretical Environment} \label{sec:theo_res}
\subsubsection{Results for the Theoretical Automobile Environment} \label{sec:theo_res}
Using the experimental setup described in Section \ref{sec:test-platform} on the platform described at the beginning of Section \ref{sec:test-platform}, results were collected in regards to the effect of synchronous firing on both state space and runtime. The graphs' edge to state ratio (E/S Ratio) was computed as well. The inclusion of this ratio allows for a comparison to be drawn regarding the usage of the synchronous firing feature. Examining this ratio can provide additional insight on how the graph's underlying topological structures change when using or not using synchronous firing. The results can be seen in Figures \ref{fig:Sync-RT} and \ref{fig:Sync-State}. The respective tables are seen in Tables \ref{table:NS-Table} and \ref{table:S-Table}. Both figures show a decrease in the number of states and a decrease in the runtime when synchronous firing is utilized. Since synchronous firing prevents the generation of unattainable states, there is no meaningful information loss that occurs in the graphs generated with the synchronous firing feature. Since the resulting number of states was also reduced, there will be increased justification for the synchronous firing approach due to a reduced runtime for the analysis process. Fig. \ref{fig:Sync-Spd} displays the speedup (according to Amdahl's Law) obtained when using synchronous firing instead of non-synchronous firing for identical setups.
When examining the E/S Ratio for the non-synchronous graphs, it is both expected and observed that the ratio slightly increases as the number of services increases. When more applicable exploits are used during the generation process, the number of permutations increases, which corresponds with the growing number of states and edges. However, the increase in the number of services also increases the relation between states and the new permutations.
@ -271,7 +293,7 @@ When comparing the E/S Ratio for the non-synchronous graphs to the E/S Ratio for
\end{tabular}
\end{table}
\subsubsection{Results for a Grouped Environment}
\subsubsection{Results for a Grouped Automobile Environment}
The environment and resulting graphs presented in Section \ref{sec:theo_res} depict the possible states of the two cars in compliance graph formats. While these graphs demonstrated accurate, exhaustive depictions of the cars and their compliance standings, they may not be realistic representations of the most likely outcomes. If a car was due for two compliance checks at the same time, it is unlikely that the car would be taken for one maintenance, returned to its original destination, then driven immediately back for maintenance, and finally to its original destination once more. The more realistic scenario is that the car is taken for maintenance, both services are performed at the same visit, and then the car is returned to its original destination.
Another set of graphs were generated using only the 3-Service case. These services were for a driveshaft boot check, an AC filter change, and an oil change. This set of graphs used `comprehensive services", where a car would undergo multiple services simultaneously. With three services used, there are a total of three permutations: all three services are done individually, two services are performed simultaneously while the other is performed later, and all three services are performed simultaneously.
@ -352,6 +374,8 @@ Leveraging comprehensive services with synchronous firing enables users to signi
\label{fig:Comp-Sync-Spd}
\end{figure}
\subsubsection{Results for the DMCA Takedown Environment} \label{sec:dmca_res}
Using the experimental setup described in Section \ref{sec:test-platform} on the platform described at the beginning of Section \ref{sec:test-platform}, results were collected in regards to the effect of synchronous firing on both state space and runtime. The graphs' edge to state ratio (E/S Ratio) was computed as well.
\section{Future Works} \label{sec:fw}
As seen and discussed in Section \ref{sec:inseparable}, when unattainable states are generated, there is a compounding effect. Each unattainable state is explored, and is likely to generate additional unattainable states. Future works include examining the effect of synchronous firing when more assets are utilized. It is hypothesized that the synchronous firing approach will lead to an increased runtime reduction and state space reduction due to the increased number of unattainable state permutations. This work had a limited number of assets, but generated upwards of 400,000 states due to repeated applications of the exploit set due to the services corresponding with the compliance graph. Future work could alter the scenario to have a greater number of assets, and a standard set of exploits more akin to an attack graph rather than a compliance graph. Other future works could include measuring the performance of synchronous firing when multiple groups of inseparable features are used. This work used a single group, but multiple groups be added to examine the performance of the feature.

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@ -91,6 +106,10 @@
\bibcite{louthan_hybrid_2011}{16}
\bibcite{cook_rage_2018}{17}
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@ -92,4 +92,20 @@ W.~M. Nichols, {\em {Hybrid} {Attack} {Graphs} for {Use} with a {Simulation} of
a {Cyber-Physical} {System}}.
\newblock PhD thesis, The {University} of {Tulsa}, 2018.
\bibitem{DMCA}
``H.r.2281 - {Digital {Millennium} {Copyright} {Act}}.''
\newblock Pub. L. No. 105-304. 1998 [Online]. Available:
https://www.govinfo.gov/content/pkg/PLAW-105publ304/html/PLAW-105publ304.htm.
\bibitem{Piracy}
Y.~Kim, J.~Moon, S.~J. Cho, M.~Park, and S.~Han, ``Efficient identification of
windows executable programs to prevent software piracy,'' in {\em 2014 Eighth
International Conference on Innovative Mobile and Internet Services in
Ubiquitous Computing}, pp.~236--240, 2014.
\bibitem{Android_Piracy}
N.~Kumari and M.~Chen, ``Malware and piracy detection in android
applications,'' in {\em 2022 IEEE 5th International Conference on Multimedia
Information Processing and Retrieval (MIPR)}, pp.~306--311, 2022.
\end{thebibliography}

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@ -1,7 +1,7 @@
\documentclass{IEEEoj}
%DIF LATEXDIFF DIFFERENCE FILE
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%DIF ADD Schrick-Noah_AG-CG-SyncFire_Revised.tex Tue Feb 28 13:35:09 2023
%DIF ADD Schrick-Noah_AG-CG-SyncFire_Revised.tex Wed Mar 22 18:17:56 2023
\usepackage{cite}
\usepackage{spverbatim}
\usepackage{amsmath,amssymb,amsfonts}
@ -19,11 +19,11 @@
\RequirePackage{color}\definecolor{RED}{rgb}{1,0,0}\definecolor{BLUE}{rgb}{0,0,1} %DIF PREAMBLE
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@ -255,7 +255,8 @@ All data was collected on a 13 node cluster, with 12 nodes serving as dedicated
\end{itemize}
All nodes are connected with a 10Gbps Infiniband interconnect.
The example networks for testing the effectiveness of synchronous firing follow the compliance graph generation approach. These networks analyze two assets, both of which are identical 2006 Toyota Corolla cars with identical qualities. The generation examines both cars at their current states, and proceeds to advance in time by a pre-determined amount, up to a pre-determined limit. Each time increment updates each car by an identical amount of mileage. During the generation process, it is determined if a car is out of compliance either through mileage or time since its last maintenance in accordance with the Toyota Corolla Maintenance Schedule manual.
\DIFaddbegin \subsubsection{\DIFadd{Automobile Maintenance}}
\DIFaddend The example networks for testing the effectiveness of synchronous firing follow the compliance graph generation approach. These networks analyze two assets, both of which are identical 2006 Toyota Corolla cars with identical qualities. The generation examines both cars at their current states, and proceeds to advance in time by a pre-determined amount, up to a pre-determined limit. Each time increment updates each car by an identical amount of mileage. During the generation process, it is determined if a car is out of compliance either through mileage or time since its last maintenance in accordance with the Toyota Corolla Maintenance Schedule manual.
In addition, the tests employ the use of ``services", where if a car is out of compliance, it will go through a correction process and reset the mileage and time since last service. Each test varies in the number of services used. The 1 Service case only employs one service, and it is dedicated to brake pads. The 2-Service case employs two services, where the first service is dedicated to the brake pads, and the second is for exhaust pipes. This process extends to the 3-, 4-, 5-, and 6-Service cases.
The experimental setup is as follows:
@ -279,8 +280,37 @@ The compliance checks are as follows:
\item{Driveshaft boots: to be checked every 12,000 miles}
\end{itemize}
\subsection{Results and Analysis}
\subsubsection{Results for the Theoretical Environment} \label{sec:theo_res}
\DIFaddbegin \subsubsection{\DIFadd{DMCA Takedown}}
\DIFadd{A second example of synchronous firing is illustrated through a DMCA Takedown for a fictitious organization \mbox{%DIFAUXCMD
\cite{DMCA}}\hskip0pt%DIFAUXCMD
. In this example, a DMCA Takedown is issued to an organization after a group of employees were found to be engaging in online piracy with torrenting software on company devices and using company resources. Detection and removal of illicit data, such as through means presented by the authors of \mbox{%DIFAUXCMD
\cite{Piracy} }\hskip0pt%DIFAUXCMD
for Windows or \mbox{%DIFAUXCMD
\cite{Android_Piracy} }\hskip0pt%DIFAUXCMD
for company-supplied Android mobile devices, can be incorporated into and represented by a compliance graph.
}
\DIFadd{Only the subset of the organization's network which contains the illicit data is used for this example. The graph generation process walks through as a system administrator removes the torrenting software and the illicit data from the company devices. When removing torrenting software, the data associated with the torrenting program can be removed at the same time; an administrator does not need to remove the torrenting program and then separately remove the data. This example highlights the capability of synchronous firing by grouping the removal of software and data together, as opposed to traditional attack and compliance graphs requiring at least two separate steps to remove the software and data.
}
\DIFadd{This experimental setup is as follows:
}\begin{itemize}
\item{Employee A has torrenting software, and is actively uploading and downloading 3 programs.}
\item{Employee B has torrenting software, and is actively uploading and downloading 4 programs.}
\item{Employee C has torrenting software, and is actively uploading and downloading 7 programs.}
\item{If synchronous firing is not enabled, the administrator removes each illicit program one-by-one after the removal of the torrenting software.}
\item{If synchronous firing is enabled, the administrator removes the torrenting software and all programs off a single device simultaneously.}
\item{Graph visualization was not timed. Only the generation and database operation time was measured.}
\end{itemize}
\DIFadd{The compliance checks are as follows:
}\begin{itemize}
\item{Does an employee have torrenting software}
\item{Does an employee have illicit data}
\end{itemize}
\DIFaddend \subsection{Results and Analysis}
\subsubsection{Results for the Theoretical \DIFaddbegin \DIFadd{Automobile }\DIFaddend Environment} \label{sec:theo_res}
Using the experimental setup described in Section \ref{sec:test-platform} on the platform described at the beginning of Section \ref{sec:test-platform}, results were collected in regards to the effect of synchronous firing on both state space and runtime. The graphs' edge to state ratio (E/S Ratio) was computed as well. The inclusion of this ratio allows for a comparison to be drawn regarding the usage of the synchronous firing feature. Examining this ratio can provide additional insight on how the graph's underlying topological structures change when using or not using synchronous firing. The results can be seen in Figures \ref{fig:Sync-RT} and \ref{fig:Sync-State}. The respective tables are seen in Tables \ref{table:NS-Table} and \ref{table:S-Table}. Both figures show a decrease in the number of states and a decrease in the runtime when synchronous firing is utilized. Since synchronous firing prevents the generation of unattainable states, there is no meaningful information loss that occurs in the graphs generated with the synchronous firing feature. Since the resulting number of states was also reduced, there will be increased justification for the synchronous firing approach due to a reduced runtime for the analysis process. Fig. \ref{fig:Sync-Spd} displays the speedup (according to Amdahl's Law) obtained when using synchronous firing instead of non-synchronous firing for identical setups.
When examining the E/S Ratio for the non-synchronous graphs, it is both expected and observed that the ratio slightly increases as the number of services increases. When more applicable exploits are used during the generation process, the number of permutations increases, which corresponds with the growing number of states and edges. However, the increase in the number of services also increases the relation between states and the new permutations.
@ -357,7 +387,7 @@ When comparing the E/S Ratio for the non-synchronous graphs to the E/S Ratio for
\end{tabular}
\end{table}
\subsubsection{Results for a Grouped Environment}
\subsubsection{Results for a Grouped \DIFaddbegin \DIFadd{Automobile }\DIFaddend Environment}
The environment and resulting graphs presented in Section \ref{sec:theo_res} depict the possible states of the two cars in compliance graph formats. While these graphs demonstrated accurate, exhaustive depictions of the cars and their compliance standings, they may not be realistic representations of the most likely outcomes. If a car was due for two compliance checks at the same time, it is unlikely that the car would be taken for one maintenance, returned to its original destination, then driven immediately back for maintenance, and finally to its original destination once more. The more realistic scenario is that the car is taken for maintenance, both services are performed at the same visit, and then the car is returned to its original destination.
Another set of graphs were generated using only the 3-Service case. These services were for a driveshaft boot check, an AC filter change, and an oil change. This set of graphs used `comprehensive services", where a car would undergo multiple services simultaneously. With three services used, there are a total of three permutations: all three services are done individually, two services are performed simultaneously while the other is performed later, and all three services are performed simultaneously.
@ -437,7 +467,11 @@ Leveraging comprehensive services with synchronous firing enables users to signi
\caption{Speedup (Amdahl's) Obtained When Using Synchronous Firing with Comprehensive Services}
\label{fig:Comp-Sync-Spd}
\end{figure}
\DIFaddbegin
\subsubsection{\DIFadd{Results for the DMCA Takedown Environment}} \label{sec:dmca_res}
\DIFadd{Using the experimental setup described in Section }\ref{sec:test-platform} \DIFadd{on the platform described at the beginning of Section }\ref{sec:test-platform}\DIFadd{, results were collected in regards to the effect of synchronous firing on both state space and runtime. The graphs' edge to state ratio (E/S Ratio) was computed as well.
}\DIFaddend
\section{Future Works} \label{sec:fw}
As seen and discussed in Section \ref{sec:inseparable}, when unattainable states are generated, there is a compounding effect. Each unattainable state is explored, and is likely to generate additional unattainable states. Future works include examining the effect of synchronous firing when more assets are utilized. It is hypothesized that the synchronous firing approach will lead to an increased runtime reduction and state space reduction due to the increased number of unattainable state permutations. This work had a limited number of assets, but generated upwards of 400,000 states due to repeated applications of the exploit set due to the services corresponding with the compliance graph. Future work could alter the scenario to have a greater number of assets, and a standard set of exploits more akin to an attack graph rather than a compliance graph. Other future works could include measuring the performance of synchronous firing when multiple groups of inseparable features are used. This work used a single group, but multiple groups be added to examine the performance of the feature.

28
OJ_Template/Original Submission/Bibliography.bib
View File

@ -210,3 +210,31 @@ pages = {},
title = {Analysis of Attack Graph Representations for Ranking Vulnerability Fixes},
doi = {10.29007/2c1q}
}
@misc{DMCA,
title = {H.R.2281 - {Digital {Millennium} {Copyright} {Act}},
note = {Pub. L. No. 105-304. 1998 [Online]. Available: https://www.govinfo.gov/content/pkg/PLAW-105publ304/html/PLAW-105publ304.htm},
}
@inproceedings{Piracy,
author={Kim, Yesol and Moon, Jeongoh and Cho, Seong Je and Park, Minkyu and Han, Sangchul},
booktitle={2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing},
title={Efficient Identification of Windows Executable Programs to Prevent Software Piracy},
year={2014},
volume={},
number={},
pages={236-240},
doi={10.1109/IMIS.2014.29}
}
@inproceedings{Android_Piracy,
author={Kumari, Neha and Chen, Min},
booktitle={2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR)},
title={Malware and Piracy Detection in Android Applications},
year={2022},
volume={},
number={},
pages={306-311},
doi={10.1109/MIPR54900.2022.00061}}