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DSD/qrs/main.tex

@@ -130,7 +130,6 @@ The two case studies presented in section~\ref{sec:cs1} and~\ref{sec:cs2} illust
 Finally, we will discuss some important aspects of the proposed solution in Section~\ref{sec:discussion}.
 
 \section{Related Work}\label{sec:related}
-\agd{add something about STL}
 Side-channel analysis focuses on extracting information from the involuntary emissions of a system.
 This topic traces back to the seminal work of Paul C. Kocher.
 He introduced power side-channel analysis to extract secrets from several cryptographic protocols \cite{kocher1996timing}.
@@ -233,7 +232,7 @@ The sample receives the label $j$ associated with the pattern $P_j$ that results
 The minimum distance from the pattern $P_j$ to all other patterns $P_l$ with $l\neq i$ --- denoted $ID_j$ --- forms the basis of the threshold $T_j$.
 Intuitively, the patterns in $P$ represent most of the patterns expected in the trace.
 Thus, to decide that a substring matches a pattern $P_j$, it must match $P_j$ better than any other pattern $P_l$ with $l\neq i$ does.
-Otherwise, the distance metric justifies assigning the label of $P_j$ to a pattern of another label instead of the substring, which is counter-intuitive.\agd{make explanation better}
+Otherwise, suggest assigning the substring to $P_j$ when the training pattern of another class matches $P_j$ better, which is counter-intuitive.
 The inter-distance between $P_j$ to $P_l$, defined as
 \begin{equation}
 ID(P_j,P_l) = \min_{i\in[0,N_l-N_j]} nd(P_j,P_l[i:i+N_j])