grizzly/deneir
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

camera ready DSD qrs

Browse source
This commit is contained in:
Arthur Grisel-Davy 2023-09-25 09:28:45 -04:00
parent f4eec6ea31
commit 40c54e53a7
3 changed files with 19 additions and 13 deletions
Download patch file Download diff file Expand all files Collapse all files

3
.gitignore vendored
View file

@ -30,3 +30,6 @@
# markdown files
*.md
# archives
*.zip

7
DSD/qrs/biblio.bib
View file

@ -103,8 +103,11 @@ series = {MobiSys '17}
title = {Reference hidden for peer-review},
}
@misc{hidden-articlemlcs,
title = {Reference hidden for peer-review},
@misc{articlemlcs,
title = {Side-channel Based Runtime Intrusion Detection for Network Equipment},
author = {Arthur Grisel-Davy, Goksen U. Guler, Julian Dickert, Philippe Vibien, Waleed Khan, Jack Morgan, Carlos Moreno, and Sebastian Fischmeister},
year = {2023},
Journal = {Machine Learning for Cyber Security. ML4CS 2023}
}
@inbook{278e1df91d22494f9be2adfca2559f92,

22
DSD/qrs/main.tex
View file

@ -32,16 +32,16 @@
\begin{document}
\input{acronyms}
\title{\textbf{\Large MAD: One-Shot Machine Activity Detector for Physics-Based Cyber Security\\}}
%\author{
% Arthur Grisel-Davy$^{1,*}$, Sebastian Fischmeister$^{1}$\\
% \normalsize $^{1}$University of Waterloo, Ontario, Canada\\
% \normalsize agriseld@uwaterloo.ca, sfishme@uwaterloo.ca\\
% \normalsize *corresponding author
%}
\author{
\vspace{\baselineskip}
\vspace{1.1\baselineskip}
Arthur Grisel-Davy$^{1,*}$, Sebastian Fischmeister$^{1}$\\
\normalsize $^{1}$University of Waterloo, Ontario, Canada\\
\normalsize agriseld@uwaterloo.ca, sfishme@uwaterloo.ca\\
\normalsize *Corresponding author
}
%\author{
% \vspace{\baselineskip}
% \vspace{1.1\baselineskip}
%}
%+++++++++++++++++++++++++++++++++++++++++++
% use only for invited papers
@ -127,7 +127,7 @@ In experiments, \gls{mad} outperforms other approaches in accuracy and the reduc
We will present the current related work on physics-based security and time series pattern detection in Section~\ref{sec:related}.
Then we will introduce the formal and practical definitions of the solution in Section~\ref{sec:statement} and~\ref{sec:solution}.
The two case studies presented in section~\ref{sec:cs1} and~\ref{sec:cs2} illustrate the performances of the solution in various situations.
The two case studies presented in Section~\ref{sec:cs1} and~\ref{sec:cs2} illustrate the performances of the solution in various situations.
Finally, we will discuss some important aspects of the proposed solution in Section~\ref{sec:discussion}.
\section{Related Work}\label{sec:related}
@ -141,7 +141,7 @@ Acoustic emissions \cite{belikovetsky2018digital}, heat pattern signature \cite{
Side-channel information collection generally results in time series objects to analyze.
There exists a variety of methods for analyzing time series.
For signature-based solutions, a specific extract of the data is compared to known-good references to assess the integrity of the host \cite{9934955, hidden-articlemlcs}.
For signature-based solutions, a specific extract of the data is compared to known-good references to assess the integrity of the host \cite{9934955, articlemlcs}.
This signature comparison enables the verification of expected and specific sections and requires that the sections of interest can be extracted and synchronized.
Another solution for detecting intrusions is the definition of security policies.
Security policies are sets of rules that describe wanted or unwanted behavior.
@ -514,7 +514,7 @@ The dataset is publicly available \cite{zenodo}.
\textbf{Lab Captures:}
NUCPC-0, NUCPC-1, WAP-ASUS and WAP-LINKSYS correspond to lab-captured machine activity power consumption.
A commercial solution \cite{hidden-palitronica}, placed in series with the main power cable, measures the global power consumption of the machine.
A commercial solution \cite{palitronica}, placed in series with the main power cable, measures the global power consumption of the machine.
We considered two types of machines.
The NUCPC-* are small form factor general-purpose computers.
The WAP-* are wireless access points from two different brands.