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TOIFAS/data/verify_math.csv
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KiHoLee 3a9a5eebf4 Key-space attacks against both key families, and the learned SNR sweep
check_family_enum.py now runs both attacks against both families. The
outsider ranks the L-1 Walsh rows; the insider, holding m_v, ranks the
L-1 products m_v .* m_r, which works because Walsh rows are closed
under the elementwise product and the per-block sign cancels in
m_u .* m_v. Both need a list to rank, and only the structured family
supplies one: the structured family falls at 0.905 from one frame at
10 dB and 0.990 from four, the refresh takes the outsider to 0.000 and
leaves the insider at 0.980, and the learned family gives 0.000
throughout.

exp_full.stage_N sweeps the learned family over the same SNR grid at
the same frame count as stage_A, so Fig. 2 can carry both families and
a reader can see what the key space costs at every SNR rather than at
one point.

check_consistency.py gains four assertions for the key-space
measurements and two for the learned sweep, 82 in all.

README: the assertion count was two rounds stale, and the figure map
omitted family_enum, cov_attack and maskdegen, whose CSVs back quoted
manuscript numbers.
2026-08-28 19:30:58 +09:00

1.3 KiB

1checkclaimempiricalabs_errtolverdict
2V1 legit self-alignment1.00.99947240714247320.0005275928575267930.02PASS
3V2a eve mean advantage0.00.00064699829360976430.00064699829360976430.003PASS
4V2b eve SER @ 0dB0.996093750.9950.00109375000000000440.015PASS
5V2b eve SER @ 10dB0.996093750.98883333333333330.0072604166666666580.015PASS
6V2b eve SER @ 20dB0.996093750.98816666666666660.0079270833333333620.015PASS
7V2b eve SER @ 80dB0.996093750.98966666666666670.00642708333333330550.015PASS
8V3a bias slope in kappa1.00.99320.00680.03PASS
9V3b random mask E|corr|0.099735570100358180.101870427714086860.0021348576137286830.002992067103010745PASS
10V4a blind jammer projection mean0.00.000263961072846736950.000263961072846736950.003PASS
11V4b blind jammer projection variance0.015585762335687030.0154767879532789940.000108974382408035320.0001558576233568703PASS
12V5 matched bias over blind RMS8.08.00.041.0PASS
13V6 coded-OMA outage @ 10 dB0.04060.04057500REFERENCE
14V7 symbolic identitiesexactexact00PASS
15V8 cross-period remainder0.00.0003370.0003370.0005PASS
16V9 score-variance ratio2.82.82520.02520.05PASS
17V10 format-matched OMA at 10 dB0.0550.055200.000200.001PASS
18V11 OMA closed form vs Monte Carlo0.0811180.0809250.00240.01PASS