start conclusion of futur work
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@ -138,4 +138,11 @@ As long as the capture architecture (i.e., what machine is monitored by which ca
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In the case where the capture architecture is unknown, the problem become out of scope for this thesis.
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In the case where the capture architecture is unknown, the problem become out of scope for this thesis.
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\section{Conclusion}
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\section{Conclusion}
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\agd{to be filled}
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The main problem is conceptually simple: identify machine activity from their power consumption to detect abnormal or forbidden activities.
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The ability to interpret power consumption time series as higher-level events enables the definition of security-related rules.
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The simplest form of this problem consist in measuring the global consumption of one simple devices as a univariate time-series (SSSM problem).
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This problem lead to the developement of the \gls{dsd} which can already recognize some activity patterns from a machine.
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However, the potential of this idea does no stop at the SSSM problem.
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By capturing multiple consumptions from specific components from a machine (MSSM problem), the detection algorithm should support the detection of more granular activity.
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Complementarily, measuring the aggregated consumption of multiple machines as a single time series offers powerfull applications.
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