Learned-key sensitivity, brute-force and real-token stages; legend order

exp_learned.py completes the learned side of the result stages, so every
figure can carry both realizations of keyed masking. real() holds the
structured artifacts aside and restores them, since exp_real_sec writes
fixed file names.

replot_security.py ranks legend handles from one declared order at all
three ax.legend call sites, so entries no longer follow plot-call order
and drift between figures.

code/make_tables.py

@@ -11,8 +11,8 @@ from pathlib import Path
 DATA = Path(__file__).resolve().parents[1] / "data"
 
 NAME = {
-    "proposed": r"\textbf{KM (structured)}",
-    "proposed_learned": r"\textbf{KM (learned)}",
+    "proposed": r"\textbf{KM (str.)}",
+    "proposed_learned": r"\textbf{KM (lrn.)}",
     "public_mask": "Public masks",
     "perm_key": r"Permutation key~\cite{chen2025shufflingtifs}",
     "index_cipher": "Index cipher",
@@ -21,7 +21,7 @@ NAME = {
     "hadamard": "Structured",
     "learned": "Learned, plain",
     "learned_reg": r"Learned, regularized~\eqref{eq:regloss}",
-    "invariant_learned": r"\textbf{Invariant, learned keys}",
+    "invariant_learned": r"\textbf{Invariant, KM (lrn.)}",
 }
 RECEIVER = {
     "legit": "Legitimate", "oma": "OMA",