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

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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.
This commit is contained in:
KiHoLee
2026-08-28 20:31:50 +09:00
parent c00e8ab666
commit 669737e83d
16 changed files with 210 additions and 26 deletions
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data/refresh_summary.csv
+2 -2
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@@ -1,5 +1,5 @@
scheme,legit,eve,entropy_bits
None (fixed key),0.05300666667,0.9997075,23.76910417
Fresh orthogonal keys,0.1215548611,0.9996535069,23.76910417
Invariant,0.05304121528,0.9995528819,364.5801064
"Invariant, learned keys",0.063800,0.997200,364.5801064
"Invariant, KM (str.)",0.05304121528,0.9995528819,364.5801064
"Invariant, KM (lrn.)",0.063800,0.997200,364.5801064
1 scheme legit eve entropy_bits
2 None (fixed key) 0.05300666667 0.9997075 23.76910417
3 Fresh orthogonal keys 0.1215548611 0.9996535069 23.76910417
4 Invariant Invariant, KM (str.) 0.05304121528 0.9995528819 364.5801064
5 Invariant, learned keys Invariant, KM (lrn.) 0.063800 0.997200 364.5801064