\chapter{Conclusion}
The problem of leveraging power side-channel analysis to defend embedded system present unique capabilities.
In opposition with current common \gls{ids} techniques, physics-based security is not built on purpose-made actionable data.
The very nature of the input information sets this techniques aside.
Power consumption is closely related to instruction execution, and makes it a good proxy variable for machine activity.
Moreover, power is easy and cheap to measures reliably at a high sampling rate, enabling analysis of any machine consuming electricity.
Finally, a sequence of instructions is generally related to a unique power consumption pattern.
This \textit{one-to-one} relationship, allows to consider the power consumption as a signature for a software of machine activity.
However, power consumtion is not an actionable information.
From the raw time series format, little can be extracted about the machine activity or integrity. 
To enable further analysis, a set of algorithm is required for both runtime online analysis as well as offline monitoring of specific activity.
The full range of capabilities is still unknown.
Successfull runtime monitoring enables the detection of activity policy violation, anomalous activity detection, machine failure detection or distributed attacks.
On the other hand, pre-OS monitoring enable the detection of boot process violation at a level where common \gls{ids} are not enabled yet.
These are just some of the possible applciation of this technology, with many more to be discovered.

With this proposal, I present some problems to study that enables some of the applications of physics-based security.
I hereby ask to continue researching these problems with the view to complete my PhD thesis.
