Topic: Pollard's kangaroo ECDLP solver - page 119. (Read 60624 times)

Hardware, how long are you running your precomp for? You have a set # of DPs or a percentage? 2/3 ops?

the 64 bit doesn't need to equal anything...
it could be a sequential 40, 41, 42, 50, 56, 72, 80, etc bit range. The object is to check the smaller ranges (subgroups?) inside a larger range for the same key.

I think if you fined key in 64 bit, you not need next 64 bit, but if you fined only on 3*64 bits false and after only 1  BINGO 64 bit, this is I  think not = 256 bytes key and fourth 64 bits with private key will be not 256 bytes key too.........

Jean Luc...your Kangaroo is now a fast solver...especially for the lower bits, 90 on down. I know the higher the bits the longer it takes to solve. But what can you do from this point forward to make solving the higher bits, optimized/faster?

In all the articles and research papers I have read, well most of them, they talk about subgroups. Can this not be done?

Example, if we are trying to solve a key for the range 10000:1FFFF, currently we can only use the exact range started with for the same key. Can we not setup hash and jump table for 10000:1FFFF (precomp of sorts) and then attack the range with different starting points?

Example:
1 - 10000:1FFFF
2 - 11000:1FFFF
3-  12000:1FFFF
....
10- 1A000-1FFFF

or attack in smaller bits such as

100FF-1100
101FF-1200
etc?

My PC alone can solve 64 bit in 1 minute...what if we randomly generate 64 bit (or whatever bit number desired) inside the larger bit range and use the
-m option to stop the search in this section and move to the next randomly generated 64 bit piece. or better yet, make it a sequential 64 bit search inside of a 110 bit range. With numerous GPUs, you could assign each one a different range so the sequential piece is sped up.
Example:
gpu 1- attacking 10000-11000 in smaller sequential bits
gpu 2- attacking 11001-12000 in smaller sequential bits
etc

Anyone, thoughts?

I tested dir merge on PC with 24GB RAM and 10 dir files that were probably 500MB a piece but I didn't check the RAM usage.

Alek76's version is similar to what you are talking about as far as separating files. He has (in current version) 8 text files that are generated, 4 tames and 4 wild. I modified it a little bit and used 2 tames and 4 wilds. Then, he has a python comparator that compares all the files to check for a solved key. I tried/trying to figure out how to merge that with JP's (this) version, but can't figure out how to read the files well enough to understand how to build the python comparator.

" and also the ability to reuse the Tame Kangaroos for multiple key searches. "

can we aspect multi pubkeys support coming, maybe yes or maybe no, its all depand dev thinking, maybe he prefer to work a lot more calc for client/server, or maybe he he think add this func and then optimize all thing togather

It is not a problem, if CRC32 invalid, that file will be send in next time.

been seeing this one.
1:30:21  [GETWORK] INVALID CRC32 FILE > NEED:ffffffffd52c4232, GOT:79ffe57 is this still ok. thanks man, great piece.

I was testing "directory merge" function and RAM memory is quickly exhausted. I was thinking that I forgot to free temp HashTable in each reading iteration; but I changed the code and the problem remains
The merged saveFile is 5GB, and in merge process takes up about 14GB of RAM.

I think the more obvious solution is to sort files from bigger to smallest when are merged; or use only small saveFiles.


On the other hand, the -ws flag I think is problematic when using -wsplit, generating larger files than necessary. Do you think it is interesting to separate the DP and the kangaroos into different save files?


As next improvements, I will work on improving the export of the DPs and the possibility of modifying the DP bits in a save file to reduce its size if we have chosen a too low DP value. It can also be interesting to remove from a save file the distances to share it without gifting the prize.

i was try several times but got this
try now dp=31 https://drive.google.com/file/d/1zmrmcQJ3NSbwnF2AJ4RH-vbab0VOgJSt
dp=28 https://drive.google.com/file/d/1eZNnWJnNdRhWp-ZnaxYhwfRVKZHiadEg

I also shared some files earlier.
Can you please upload your files to here: https://gofile.io
You can do it without registration, and you can delete them with your admin link at any time. Unfortunately google does not allow do download your file without google account.

I did not lose any DPs, they are only reduced to 28bit. Somewere i have file with dp=31, if you need i can share
There is link to DP=31 file https://drive.google.com/file/d/1zmrmcQJ3NSbwnF2AJ4RH-vbab0VOgJSt

P.S. If somebody can share  work it will be good. Maybe one of us can solve key in this way.

Did you lose all the DPs @ 31, when you dropped to 28?

Here is my merged workfile for pazzle#110(109bit)
https://drive.google.com/file/d/1eZNnWJnNdRhWp-ZnaxYhwfRVKZHiadEg
DP=28. there is not so many DPs because i start with DP=31(collected half of expected Dps) than drop to 28.
Maybe somebody it can help to solve key.

I'll have to digest this the SAME value is throwing me off a little. It makes sense by what you said; you subtracted the 20000....from both values to get 0 and the 1ffff...
What is the advantage or purpose of shifting?

As far as ranges, I'm good with either, hex or powers, just wanted to keep it simple (for me, maybe for others) since we input a range start and range end on the input file versus a -bits flag.

The range is shifted, not expanded. Shift means the move of start and end values both by the SAME value.
Instead of range [2000000000000000000000000000 ... 3fffffffffffffffffffffffffff] the program works with range [0 ... 1fffffffffffffffffffffffffff]

PS. Do you really like these hex values posted here? They are difficult to understand by a human (as difficult to count "f" and "0" signs). So i represented them earlier by the powers of 2 (2^109 and 2^110) which is much easier to understand.

Can you help make it clear to me

So the tames work from range 0...meaning 0x0 to 0x3FFFFFFFFFFFFFFFFFFFFFFFFFFFF  (for pubkey 110)?

thanks for answer.
Also can say, that i was made test with previous experience work.
And I can disappoint that it turned out to be slower..
I started to gain experience with the puzzle 54
do job>save work file>separated the tame kangaroos and kept in a new work file(I did not tame wild kangaroos)
This work file was as input for next pazzle..and so on to pazzle 84.
I also launched the same puzzles but without previous experience.
And always in 100% of cases, the key was found faster without using experience.

Because the Tame Kangaroos are dependent only on the interval size, while the Wild Kangaroos are dependent on the interval size and the public key. We want to keep the algorithm as generic as possible, and also the ability to reuse the Tame Kangaroos for multiple key searches.

As relating to the Wild Kangaroos, [working_public_key] = [(original_public_key) - (beginning_range)*(secp256k1_generator_point)].
[distinguished_point] = [(+-traveled_distance)*(secp256k1_generator_point)] + [working_public key]

You will need to add back the (beginning_range) when there’s a collision to solve for the (original_public_key).

Thanks for the detailed answer. This is very clear now.