From 671b444f61b302cd6d9b41dad03242ba75a311f6 Mon Sep 17 00:00:00 2001 From: Arthur Grisel-Davy Date: Wed, 21 Jun 2023 16:31:02 -0400 Subject: [PATCH] start conclusion of futur work --- PhD/research_proposal/futurwork.tex | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/PhD/research_proposal/futurwork.tex b/PhD/research_proposal/futurwork.tex index 21dd6dd..d4daec0 100644 --- a/PhD/research_proposal/futurwork.tex +++ b/PhD/research_proposal/futurwork.tex @@ -138,4 +138,11 @@ As long as the capture architecture (i.e., what machine is monitored by which ca In the case where the capture architecture is unknown, the problem become out of scope for this thesis. \section{Conclusion} -\agd{to be filled} +The main problem is conceptually simple: identify machine activity from their power consumption to detect abnormal or forbidden activities. +The ability to interpret power consumption time series as higher-level events enables the definition of security-related rules. +The simplest form of this problem consist in measuring the global consumption of one simple devices as a univariate time-series (SSSM problem). +This problem lead to the developement of the \gls{dsd} which can already recognize some activity patterns from a machine. +However, the potential of this idea does no stop at the SSSM problem. +By capturing multiple consumptions from specific components from a machine (MSSM problem), the detection algorithm should support the detection of more granular activity. +Complementarily, measuring the aggregated consumption of multiple machines as a single time series offers powerfull applications. +