Can anyone recommend a set of deciphering tests to judge whether a new ngram file is better than another one?
I’ve developed new ngram files and they seem better in my judgement, but it’s hard to quantify without a good way to measure them.
Right now, I’m seeing how short a versions of the 408 it can solve:
custom 5-gram
7 line 408 solves instantly
6 line 408 solves pretty ok
4.5 lines 408 solves with seq homophones
custom 6-gram
5 line 408 solves quickly w/ only regular solver
4.7 line 408 solves w/ regular solver after a min
4 lines 408 solves with seq homophones easy
3.5 lines 408 solve w/ seq homophones
"[The sequential homophone solver can now] Solve on a 5 row 408 with 6-grams, AZdecrypt’s previous best was 6 rows with 7-grams"
"Solve on a 6 row 408 with 5-grams, a tie with AZdecrypt’s previous best which had to use 7-grams to accomplish this"
Even if this is a good test, it’s kind of becoming hard to use as I improve my files because I’m not sure that any language model can be good enough to solve a 3 line 408.
My only other informal benchmark has been solve time for "Smokie treats: Perfect cycles + 3 high count 1:1 substitutes + 4 medium-high count wildcards/polyalphabetic symbols" w/ seq homophones:
custom 5-grams: 55 sec
custom 6-grams: 58 sec
5-gram pc: n/a
5-gram-reddit: 1:39
6-gram-reddit: 1:05
Can anyone suggest other benchmarks?
I’ve skimmed through the "Test Cipher Collection" that doranchak kindly compiled. Nothing jumps out at me as an obvious yardstick, but I don’t really know where to look:
https://docs.google.com/spreadsheets/u/ … 1394933925
It depends on whether you want to test the solverates or the speed. I test the solverates of my own solver as follows:
– Download large text base. I use https://wortschatz.uni-leipzig.de/de/download . Click on "Englisch" and download one of the 1M files (for example "News 2016" or "Wikipedia 2016").
– Open archive and extract "eng_news_2005_1M-sentences.txt".
– Load text and remove all characters except A-Z.
– Run through the entire text and cut 340 characters per run (or whatever cipher size you need).
– Apply homophonic substitution
– Now send the generated cipher to the solver and let it solve. If a defined threshold score is exceeded (e.g. 22000 for AZDecrypt), the cipher is considered as solved.
– Count how many of the generated ciphers have been solved.
– In this way you can test thousands of ciphers automatically.
– Now try the same thing with different nGram files. The number of solved ciphers determines the quality of the nGram files.
Well, that’s how I do it. With AZDecrypt this doesn’t work directly, because the solver can only be controlled via GUI. But now that the source code has been released, you could extract the solver and control it programmatically. Then you could easily perform such benchmark tests.
Great idea Largo! Solve rate against a large set of ciphers would be an excellent yardstick to quantify performance.
And I think it’s already possible to test such a set natively with AZDecrypt using the "Batch Cipher" option. There’s an example text file that tries to solve all the beale ciphers, etc in one back-to-back run. The hard part is just having a large set of ciphers that are difficult enough that they aren’t trivially solved by the reddit 5-grams or the pc 5-grams, but still solvable with stronger models. Right now, most ciphers are either instantly solved (even with the weakest n-gram models), or unsolvable with all known n-gram model.
If you can pack a few hundred (or thousand) tests into a batch cipher file, I’ll test against it to benchmark my ngram files. Would be very useful to have a large batch file with a solve rate profile like:
Prac C 5-gram : 30%
Reddit 5-gram : 40%
Reddit 6-gram : 50%
Reddit 7-gram : 60%
We just need a test where better / stronger models show clear improvement… but also one where there’s head-room for improvement.
Judging from the results on the 408, your custom n-grams seem pretty awesome beijinghouse (understatement).
Here is a cipher batch file I used. Some are more tricky and may require more specialized n-grams (names, numerals, etc…). Some unsolved are also included: 340_unknown, glurkbeale3_names, nickpelling, kenharthun and alanbenji.
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beijinghouse, could you please provide the nGram file somewhere for download? Thanks a lot!
Thanks for the cipher list Jarlve! Much appreciated. Any more like this?
Here’s a draft of my 5-gram file. I’m still tweaking it but I’m happy to share a beta with you guys.
https://rockstarresearch.com/ciphers/5- … _beta1.zip
So far it seems to perform well on a broad range of ciphers: smokie2_wildcards, tonyb2_nomenclator, largodracula, doranchak2_defects, etc.
And FWIW, I solved kenharthun with AZDecrypt + some cribbing:
IGOTAQUESTIONTOD AYOVERATASKTHEGE EKABOUTHOMOPHONI CCIPHERSSOITHOUG HTIWOULDLETYOUKN OWTHEM
Thank you very much! I’m looking forward to experimenting with it.
Thanks for sharing beijinghouse.
Your n-grams are amazing! I would like to include them with AZdecrypt when you are done with it. It seems that you filtered out the noise.
And FWIW, I solved kenharthun with AZDecrypt + some cribbing:
Very nice. How does one crib something like this? I would not know where to begin.
Your n-grams are amazing! I would like to include them with AZdecrypt when you are done with it. It seems that you filtered out the noise.
Sure, that would be OK with me.
I did a lot of filtering but they’re mostly more powerful because they are a distillation of >3TB of text. All Project Gutenberg books. Every reddit comment. Every Stack Overflow comment. Every Hacker News comment. All of Wikipedia. Every song lyric. Millions of Amazon reviews. Etc.
I also found a new way to draw in another TB of very clean new source data. So they should be significantly better in a few days (and even less correlated with the reddit ngrams, so more chance of them behaving differently with the solver). Can finalize a release for you next week if you want. Can possibly give you 6-grams and 7-grams too after that. Those work quite amazingly already and I haven’t even tuned them yet.
I’m still looking for more challenging ciphers to test them on if you have any more?
And has anyone considered using this as n-gram source data? https://www.corpusdata.org/
If anyone knows Mark Davies at BYU or has university access to his corpus data (or wants to just pay the $245-500 to buy them) it would definitely improve the quality of these ngrams.
Can finalize a release for you next week if you want. Can possibly give you 6-grams and 7-grams too after that. Those work quite amazingly already and I haven’t even tuned them yet.
Take your time. If possible I would like n-grams from 3 to 7.
I’m still looking for more challenging ciphers to test them on if you have any more?
Scorpion 5, unsolved, possibly high multiplicity homophonic:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 32 48 49 35 50 51 52 53 54 55 56 57 58 14 59 60 61 62 63 64 65 51 66 67 68 10 69 70 71 72 73 74 32 75 76 77 78 51 79 80 81 82 83 84 85 14 86 74 87 88 89 90 91 6 92 23 93 41 94 95 96 97 98 99 100 101 102 103 104 105 106 67 107 108 109 70 110 111 112 113 1 114 115 116 117 118 119 53 120 10 121 122 123 124 125 126 100 62 127 90 128 129 130 53 24 41 26 84 71 131 30 132 133 134 127 135 136 137 22 39 68 25 138 139 140 141 15 142 143 144 127 145
Also try https://ciphermysteries.com/2017/06/25/ … hers-solve
None of these have been solved and I included the easiest one with the list.
beijinghouse, I have experimented a with your nGrams and I am enthusiastic. It’s hard to believe that so much could be improved. Thank you for that valuable contribution!
I did a lot of filtering but they’re mostly more powerful because they are a distillation of >3TB of text. All Project Gutenberg books. Every reddit comment. Every Stack Overflow comment. Every Hacker News comment. All of Wikipedia. Every song lyric. Millions of Amazon reviews. Etc.
Books from project gutenberg always have the same passages at the beginning and at the end (license text and so on). Do you filter that out? I noticed that once when I compiled my own nGrams, because the frequent repetition has a distorting effect.
Books from project gutenberg always have the same passages at the beginning and at the end (license text and so on). Do you filter that out? I noticed that once when I compiled my own nGrams, because the frequent repetition has a distorting effect.
Yes, I do strip those pre-ambles and other boiler-plate out of PG. A similar thing I had to learn from experience was not to include PG’s largest "book": the entire human genome. Otherwise CTAGA, GTCGA, etc can become the highest ranking ngrams!
A similar thing I had to learn from experience was not to include PG’s largest "book": the entire human genome. Otherwise CTAGA, GTCGA, etc can become the highest ranking ngrams!
lol…well, who knows? Maybe Zodiac encoded a part of his DNA in z340, then that kind of nGrams would be helpful
5-gram files – Beta2
https://rockstarresearch.com/ciphers/5- … _beta2.zip