TOIFAS/data/sec_brute.csv at 3cf3b6c3a70dfa28d0ae87ea5d5489e7d5d8df73

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T

KiHoLee 3cf3b6c3a7 Re-run the key-length attack sweep and emphasize the main-configuration row

stage_F was missed in the structured-family regeneration, so sec_brute.csv
and sec_sens.csv still carried learned-family results. Re-running it moves
the L=16 brute-force point from 0.7495 to 0.5916, which now agrees with
sec_brute_cmp.csv rather than contradicting it.

make_tables.py bolds the Walsh-Hadamard row the way it already bolds the
proposed and invariant rows, since that family is the main configuration.

2026-08-18 08:48:41 +09:00

962 B

Raw Blame History

1	L	K	best_rho	eve_ser
2	8	1	0.2918601623	0.9945244994
3	8	10	0.6307837307	0.9550597921
4	8	100	0.8190062809	0.8147158732
5	8	1000	0.9077793813	0.5723297059
6	8	10000	0.9535904264	0.3866372342
7	8	100000	0.9757162716	0.3157766639
8	8	1000000	0.9872786315	0.2845244539
9	16	1	0.2228791779	0.9990085712
10	16	10	0.4570522499	0.9943536935
11	16	100	0.6321070191	0.9769163907
12	16	1000	0.7417848118	0.9311708657
13	16	10000	0.8164950053	0.8399011082
14	16	100000	0.8673534005	0.7274791752
15	16	1000000	0.9048131336	0.5915534824
16	32	1	0.1399813941	0.999821061
17	32	10	0.3205750013	0.9991354579
18	32	100	0.4660256564	0.996404209
19	32	1000	0.5620279439	0.991343747
20	32	10000	0.6393936736	0.9815239297
21	32	100000	0.6993164916	0.9634132739
22	32	1000000	0.7479539255	0.9349306487
23	64	1	0.0987436915	0.9999096477
24	64	10	0.2263401688	0.9997303409
25	64	100	0.3389944824	0.9991750164
26	64	1000	0.4155608514	0.9981802181
27	64	10000	0.4757575011	0.9967597446
28	64	100000	0.5299797378	0.994275692
29	64	1000000	0.5741312045	0.9910114047

962 B Raw Blame History

962 B

Raw Blame History