Merge branch 'master' of ssh://git.palitronica.com:10112/agriseldavy/writing
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@ -610,11 +610,14 @@ A power measurement device is placed in series with the main power cable of the
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The measurement devices captures the power consumption at 10 kilo-sampls per seconds.
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The pre-processing step downsamples the trace to 20 samples per seconds using a median filter.
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This step greatly reduces the measurement noise and the processing time, and increases the consistency of the results.
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The final sampling rate of 20 samples per seconds was selected empirically to be about one order of magnitude highter than the typical length of the patterns to detect (around 5 seconds).
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The final sampling rate of 20 samples per seconds was selected empirically to be around one order of magnitude highter than the typical length of the patterns to detect (around 5 seconds).
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For each comrpessed day of experiment (4 hours segment, thereafter refered as days), the \gls{mad} performs state detection and returns a label vector.
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This label vector associate a label to each sample of the power trace following the mapping: -1 is UNKNOWN, 0 is SLEEP, 1 is IDLE, 2 is HIGH and 3 is REBOOT.
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The training dataset comprise one sample per state, captured during a the run of a benchmark script that interatively place the machine in each states to detect.
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\agd{make dataset available}
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\subsection{Security Rules}
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Many rules can be imagined to describe the expected and unwanted behavior of a machine.
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System administrators can define highly specific rules to detect specific attacks or to match the typicall acticities of their infrastructure.
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We selected 4 rules (see Table~\ref{tab:rules}) that are representative of common threats on companies or administrations's \gls{it} infrastructures.
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@ -636,9 +639,12 @@ The rules are formaly defined using the \gls{stl} syntax which is bespoke for de
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\label{tab:rules}
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\end{table*}
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\subsection{Results}
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The performance measure represent the ability of the whole pipeline (\gls{mad} and rule checking) to detect anomalous behavior.
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The script on the machine generates logs that serves as ground truth to verify the results of rule checking.
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The main metrics are the \agd{name of metric chosen} for each rule (micro-\agd{name}) and the global \agd{name} (macro-\agd{name}).
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It is important to note that the attack frequency was intentionally increase compared to the expected attack frequency in the real world.
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\section{Discussion}\label{sec:discussion}
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In this section we highlight specific aspects of the proposed solution.
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21
maerospace/installation_overview.typ
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maerospace/installation_overview.typ
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#import "@preview/acrostiche:0.2.0": *
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#init-acronyms((
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"EET": ("Electromechanical Emission Tripwire",),
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"SBC": ("Single Board Computer",),
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"PoE": ("Power over Ethernet",),
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))
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#align(center)[#text(size:20pt)[EET Deployment Overview on Maerospace
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Equipement]]
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This document describes the planned installation of #acr("EET") measurement systems on Maerospace equipement.
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The goal of theis initial installation is to evaluate the potential of using power consumption measurement to protect Maerospace equipement.
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The protection capabilities may not be limited to cyber-attacks and may also include malfunctions or unforeseen behavior.
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The type of equipement is also not limited to processing servers and may include gateway computers.
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= Measurement Equipement
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The measurement equipement (thereafter refered to as the #acr("EET") box or simply the box) comprises a Hall Effect sensor, a digitizer, and a #acr("SBC").
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The box is power through #acr("PoE") and thus uses the same Ethernet cable for power and communication.
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