Ciphertext-only family enumeration, and checks that reproduce off a GPU

check_family_enum.py measures the attack the manuscript now states in
Section III-A: the winning correlation is an index-free verifier, so
ranking the 63 non-constant Walsh rows by mean winning correlation
recovers the user set from one frame in 0.905 of 200 trials at 10 dB
and from four frames in 0.990, using nothing outside the stated threat
model. Under the invariance refresh it recovers it in none, because the
entry permutation relabels the codebook the adversary must align
against.

V8 and V9 read the trained codebook through main_model(), which
retrains on every call, and a codebook trained on CUDA is not the one
trained on CPU. The shipped verify_math.csv therefore read PASS here
and FAIL for anyone running this package without a GPU. model_main.pt
is 7 KB and fixes the codebook, which is what both checks are about;
delete it to retrain. V1-V11 now pass on both.

New checks: V10, the format-matched OMA reference Section VI-B quotes,
and V11, the closed-form against Monte Carlo comparison the manuscript
claimed and never stored. V3a's bias-linearity result was computed and
printed but never written to the CSV, so the one linearity claim the
paper quotes was the one this package could not show.

check_consistency.py gains 21 assertions, covering five data files that
no assertion read (users, csi, semantic, cov_attack, sec_jam) and the
trend claims it structurally could not see, since it compared values
and not shapes.

README: the figure map named stages that do not write the artifacts
they list, so following it did not reproduce Figs. 4 and 6; the
reproduction block was five scripts short; and the refresh numbers were
from a superseded run (nearly three, 15.0 to 64.8 bits) against the
manuscript's 2.3 and 23.8 to 364.6.
This commit is contained in:
KiHoLee
2026-08-28 17:40:28 +09:00
parent 8dd70a1776
commit 17d23fa76a
9 changed files with 328 additions and 10 deletions
+3
View File
@@ -5,6 +5,7 @@ V2b eve SER @ 0dB,0.99609375,0.995,0.0010937500000000044,0.015,PASS
V2b eve SER @ 10dB,0.99609375,0.9888333333333333,0.007260416666666658,0.015,PASS
V2b eve SER @ 20dB,0.99609375,0.9881666666666666,0.007927083333333362,0.015,PASS
V2b eve SER @ 80dB,0.99609375,0.9896666666666667,0.0064270833333333055,0.015,PASS
V3a bias slope in kappa,1.0,0.9932,0.0068,0.03,PASS
V3b random mask E|corr|,0.09973557010035818,0.10187042771408686,0.002134857613728683,0.002992067103010745,PASS
V4a blind jammer projection mean,0.0,0.00026396107284673695,0.00026396107284673695,0.003,PASS
V4b blind jammer projection variance,0.01558576233568703,0.015476787953278994,0.00010897438240803532,0.0001558576233568703,PASS
@@ -13,3 +14,5 @@ V6 coded-OMA outage @ 10 dB,0.0406,0.040575,0,0,REFERENCE
V7 symbolic identities,exact,exact,0,0,PASS
V8 cross-period remainder,0.0,0.000337,0.000337,0.0005,PASS
V9 score-variance ratio,2.8,2.8252,0.0252,0.05,PASS
V10 format-matched OMA at 10 dB,0.055,0.05520,0.00020,0.001,PASS
V11 OMA closed form vs Monte Carlo,0.081245,0.080925,0.0039,0.01,PASS
1 check claim empirical abs_err tol verdict
5 V2b eve SER @ 10dB 0.99609375 0.9888333333333333 0.007260416666666658 0.015 PASS
6 V2b eve SER @ 20dB 0.99609375 0.9881666666666666 0.007927083333333362 0.015 PASS
7 V2b eve SER @ 80dB 0.99609375 0.9896666666666667 0.0064270833333333055 0.015 PASS
8 V3a bias slope in kappa 1.0 0.9932 0.0068 0.03 PASS
9 V3b random mask E|corr| 0.09973557010035818 0.10187042771408686 0.002134857613728683 0.002992067103010745 PASS
10 V4a blind jammer projection mean 0.0 0.00026396107284673695 0.00026396107284673695 0.003 PASS
11 V4b blind jammer projection variance 0.01558576233568703 0.015476787953278994 0.00010897438240803532 0.0001558576233568703 PASS
14 V7 symbolic identities exact exact 0 0 PASS
15 V8 cross-period remainder 0.0 0.000337 0.000337 0.0005 PASS
16 V9 score-variance ratio 2.8 2.8252 0.0252 0.05 PASS
17 V10 format-matched OMA at 10 dB 0.055 0.05520 0.00020 0.001 PASS
18 V11 OMA closed form vs Monte Carlo 0.081245 0.080925 0.0039 0.01 PASS