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.

data/real_sec_stats_learned.json

@@ -0,0 +1,32 @@
+{
+ "vocab_size": 30522,
+ "n_texts": 2000,
+ "frames": 24998,
+ "repeats": 8,
+ "decisions_per_point": 799936,
+ "distinct_tokens": 10486,
+ "token_collision": 0.006535221793661566,
+ "max_token_id": 29599,
+ "headlines_scored": 1948,
+ "headline_runs": 4,
+ "recovery": {
+  "20": {
+   "legit": 0.7023870636550308,
+   "eve": 0.0,
+   "insider": 0.0,
+   "oma": 0.6463039014373717
+  },
+  "24": {
+   "legit": 0.8787217659137577,
+   "eve": 0.0,
+   "insider": 0.0,
+   "oma": 0.8390657084188912
+  },
+  "28": {
+   "legit": 0.9477669404517454,
+   "eve": 0.0,
+   "insider": 0.0,
+   "oma": 0.9319815195071869
+  }
+ }
+}

data/real_sec_ter_learned.csv

@@ -0,0 +1,9 @@
+snr_db,ter_legit,ter_eve,ter_insider,ter_oma
+0,0.4516948856,0.9998824906,0.9962722018,0.5232856128
+4,0.223975418,0.9998662393,0.9947945836,0.2740881771
+8,0.09790408233,0.9997899832,0.9940332727,0.123424874
+12,0.04099952996,0.9997912333,0.9936357409,0.05201666133
+16,0.01653382271,0.9997299784,0.9935107309,0.02118419474
+20,0.006725538043,0.999737479,0.9934594768,0.008630690455
+24,0.002707716617,0.9997112269,0.9934182235,0.003452776222
+28,0.001037583007,0.9997274782,0.9934144732,0.001385110809

data/refresh_summary.csv

@@ -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

data/sec_brute_learned.csv

@@ -0,0 +1,15 @@
+K,ser_mask
+1,0.9967928683
+3,0.9934662748
+10,0.9869523182
+30,0.9769415244
+100,0.961966217
+300,0.9457608404
+1000,0.9257560018
+3000,0.8881725568
+10000,0.8471349462
+30000,0.8132026814
+65536,0.790006818
+100000,0.7797171991
+300000,0.7435325695
+1000000,0.7188559867

data/sec_sens_learned.csv

@@ -0,0 +1,14 @@
+frac,ser_mask
+0,0.9999754167
+0.2,0.9977270833
+0.4,0.9502445833
+0.6,0.6829479167
+0.75,0.31458375
+0.85,0.1250175
+0.9,0.09168625
+0.92,0.08508416667
+0.94,0.07654291667
+0.955,0.0716375
+0.97,0.06938458333
+0.985,0.06607833333
+1,0.0636775