[ARCHIVE] Bitcoin challenge discusion

[BtcMaker92]

GRID V100D-32Q   25607 / 32638MB | 4 targets 1302.53 MKey/s

[balskiy]

 standard version of the GeForce RTX 2060. -b 30 -t 512 -p 2400  620Mkey
 SUPER version of the GeForce RTX 2060.    -b 34 -t 512 -p 3000  765Mkey

Impressive performance for those RTX 2060 cards, i've just got my hands on a RTX 2080 card, but i can only squeeze approx 775 MKey/s out of it.
using -b 32 - t 512 - p 1630 (1018.0 MB) - this is just around the max of what i can do without getting out of memory errors.

As i have only 4GB of DDR4 ram in the rig used for bitcrack, i tried installing another 8GB block, which did not make any difference.
This machine is running windows 7 x64, maybe it will run better with windows 10?

Anyone else using RTX 2080 cards? please let me know how your performance is, if those 2060 cards does nearly the same im seriously thinking of swapping the 2080 card for maybe two of those instead.

you should use -b 46. since the card contains 46 SM Count
try -b 46 -t 512 -p 3000

[balskiy]

GRID V100D-32Q   25607 / 32638MB | 4 targets 1302.53 MKey/s

What is your b value? I got more than 1,500 mkeys on Tesla v100 with a value of -b 80 - t 512 -p 2800

[bulleteyedk]

 standard version of the GeForce RTX 2060. -b 30 -t 512 -p 2400  620Mkey
 SUPER version of the GeForce RTX 2060.    -b 34 -t 512 -p 3000  765Mkey

Impressive performance for those RTX 2060 cards, i've just got my hands on a RTX 2080 card, but i can only squeeze approx 775 MKey/s out of it.
using -b 32 - t 512 - p 1630 (1018.0 MB) - this is just around the max of what i can do without getting out of memory errors.

As i have only 4GB of DDR4 ram in the rig used for bitcrack, i tried installing another 8GB block, which did not make any difference.
This machine is running windows 7 x64, maybe it will run better with windows 10?

Anyone else using RTX 2080 cards? please let me know how your performance is, if those 2060 cards does nearly the same im seriously thinking of swapping the 2080 card for maybe two of those instead.

you should use -b 46. since the card contains 46 SM Count
try -b 46 -t 512 -p 3000

Thanks for updating me on the matter of those SM counts, this is new to me, I have all the time concluded that the -b parameter should be used in parallel with ROP counts, but since -b 64 wasn't giving me the best performance i lowered it with /2 going with -b 32 then... great information, thanks

Now i managed to get approx 882 MKey/s with -b 46 -t 512 - p 950 this allocates 22.374.400 starting points (853 MB) which is close to the max for me, please let me know how it's possible to allocate more RAM on the card without memory error.
Once Bitcrack runs it shows 2349/8192MB used

EDIT: in parallel im also running another Bitcrack instance on this rig with an older GTX 770 card, allocating approx 390 MB in starting points, maybe I should try to benchmark the RTX 2080 without running the other card too

EDIT2: running with only one instance of Bitcrack, i can achieve 890 MKey/s with RTX 2080 using parameters: -b 46 - t 512 -t 1000

[Magkirap]

Thanks for sharing, I guess I'll try to write some code to bruteforce some of the smallest unclaimed keys, though I don't hope to find anything, cause my CPU isn't very strong. I have a GTX 1060 gpu though, but I only know Javascript so it will be a bit hard to write a program that utilizes my gpu, but it should be possible. Should be a fun pet project that will at least provide me some experience.

there is no  more "unclaimed" keys left with a private keys in small ranges. they were all found a long time ago. now only the big ones are remaining and claiming each is getting harder exponentially as the power of 2 is incremented by one.
if you want to have fun, you can program something. i did that a while ago in c# for small ones as a "challenge" to my skills knowing there is no other reward.

Thats true it was getting harder today. I even try to solve like that one before on c# because I have a backround knowledge about programming. This challenge me a alot for I need to experiment algorithms that will solve the given probalem. I had solve several problems but sadly there was no reward also. However, it was exciting to do specially when we solve those problem that has a reward.

[Mangal99]

GTX 1660 -  4015/6144MB | 14 targets 475.38 MKey/s

[balskiy]

My new =>STABLE<= record on BitCrack :-)

https://i.ibb.co/vkmLrjy/DSC-0075.jpg

NV Tesla  || The unstable setting showed me 1615, but it jumps from 1585 every reading. ||

Hello, how do you launch bitreck on several cards at once?

[bulleteyedk]

My new =>STABLE<= record on BitCrack :-)



NV Tesla  || The unstable setting showed me 1615, but it jumps from 1585 every reading. ||

Hello, how do you launch bitreck on several cards at once?

I really don't think that is possible with the current releases, if so someone have their own build i think.

What I do is simply run another instance of Bitcrack in another CMD window, you need to run cudaInfo.exe before to know what ID each card have.
Running more instances requires some tweaking to your parameters, as the Bitcrack application sometimes (under initialising) can get an error, i think this is a memory issue, so you need to scale down parameters for each card a bit, and test that it runs properly

[bounty0z]

is there any way to expect some rang ?
and if there is any detailed tuto about using keyspace . like modify it to expect numbres

[bulleteyedk]

is there any way to expect some rang ?
and if there is any detailed tuto about using keyspace . like modify it to expect numbres

No the creator have stated it's random, so basicly what this means is that wallet64 key is to be found in the range = 0x8000000000000000:0x10000000000000000

I found this post from the author in the original thread:

This puzzle is very strange. If it's for measuring the world's brute forcing capacity, 161-256 are just a waste (RIPEMD160 entropy is filled by 160, and by all of P2PKH Bitcoin). The puzzle creator could improve the puzzle's utility without bringing in any extra funds from outside - just spend 161-256 across to the unsolved portion 51-160, and roughly treble the puzzle's content density.

If on the other hand there's a pattern to find... well... that's awfully open-ended... can we have a hint or two?

I am the creator.

You are quite right, 161-256 are silly.  I honestly just did not think of this.  What is especially embarrassing, is this did not occur to me once, in two years.  By way of excuse, I was not really thinking much about the puzzle at all.

I will make up for two years of stupidity.  I will spend from 161-256 to the unsolved parts, as you suggest.  In addition, I intend to add further funds.  My aim is to boost the density by a factor of 10, from 0.001*length(key) to 0.01*length(key).  Probably in the next few weeks.  At any rate, when I next have an extended period of quiet and calm, to construct the new transaction carefully.

A few words about the puzzle.  There is no pattern.  It is just consecutive keys from a deterministic wallet (masked with leading 000...0001 to set difficulty).  It is simply a crude measuring instrument, of the cracking strength of the community.

Finally, I wish to express appreciation of the efforts of all developers of new cracking tools and technology.  The "large bitcoin collider" is especially innovative and interesting!

[MrFreeDragon]

bounty0z, there was no some pattern. All the keys were random.
However, i made some analysis of all the private keys for the "opened" wallets, and can say that more likely the key has the following property:

Quantity on bit "1" in the key is 45%-55% from the total bit quantity

This means that for the wallet #64 the total quantity of "1"s in the key is from 29 to 35 with the leading first bit "1" (first bit is always "1" for all keys in the puzzle). To increase your chances youl should take 29-35 "1"s, randomly mix them with the remaining "0"s and you will receieve the key. The key consists from let's say 10 "1"s bit and 54 "0"s bit is not the key for #64, as here only 15% are "1"s and the majority are "0"s.

How did I receieve this? I had a look at all the private keys in BIN format, and found that the average quantity of "1" in all the keys is 51%, the total range is 40-60%, but the most likely is 45-55%. Please have a look at all the known private keys in BIN formmat and the calculation of "1"s and "0"s in them.

Code:

No. 	K%rng	1's	0's	%1's	Private Key in BIN
01  	100,00%	1	0	100%	1
02  	100,00%	2	0	100%	11
03  	100,00%	3	0	100%	111
04  	0,00%	1	3	25%	1000
05  	40,00%	3	2	60%	10101
06  	58,06%	3	3	50%	110001
07  	20,63%	3	4	43%	1001100
08  	76,38%	3	5	38%	11100000
09  	83,14%	6	3	67%	111010011
10  	0,59%	2	8	20%	1000000010
11  	12,90%	4	7	36%	10010000011
12  	31,07%	8	4	67%	101001111011
13  	27,37%	4	9	31%	1010001100000
14  	28,73%	5	9	36%	10100100110000
15  	63,99%	9	6	60%	110100011110011
16  	57,20%	8	8	50%	1100100100110110
17  	46,22%	11	6	65%	10111011001001111
18  	51,57%	6	12	33%	110000100000001101
19  	36,39%	12	7	63%	1010111010010011111
20  	64,66%	10	10	50%	11010010110001010101
21  	72,78%	11	10	52%	110111010010100110100
22  	43,41%	12	10	55%	1011011110010000001111
23  	33,49%	12	11	52%	10101010110111001010010
24  	72,00%	9	15	38%	110111000010101000000100
25  	97,80%	17	8	68%	1111110100101111011100101
26  	62,54%	11	15	42%	11010000000011001001101110
27  	66,82%	14	13	52%	110101011000011100001110101
28  	69,60%	14	14	50%	1101100100010110110011101000
29  	49,28%	16	13	55%	10111111000100101010100011110
30  	92,44%	16	14	53%	111101100101001100110101100100
31  	95,80%	21	10	68%	1111101010011111110011101000111
32  	44,05%	15	17	47%	10111000011000101010011000101110
33  	66,18%	16	17	48%	110101001011011001010100011011000
34  	64,53%	16	18	47%	1101001010011001011001000100011101
35  	17,07%	15	20	43%	10010101110110100100001000101110000
36  	23,36%	17	19	47%	100111011110100000100000101001111100
37  	45,89%	22	15	59%	1011101010111011101010110101010010011
38  	6,94%	17	21	45%	10001000111000001011111010110011010000
39  	17,77%	20	19	51%	100101101011111100000110000001111101001
40  	82,56%	22	18	55%	1110100110101110010010010011001111010110
41  	32,63%	21	20	51%	10101001110000110100110101100110001011011
42  	31,67%	19	23	45%	101010001000100001110001011000110110001111
43  	68,48%	24	19	56%	1101011110100111011001001111100010110010001
44  	75,13%	22	22	50%	11100000001010110011010110100011010110001111
45  	13,67%	19	26	42%	100100010111111001010000101000011110000000101
46  	46,11%	19	27	41%	1011101100000110000011100010001101010101000100
47  	70,06%	24	23	51%	11011001101011000010000101101010011110010111010
48  	35,86%	31	17	65%	101011011110011011010111110011100011101110011011
49  	45,35%	25	24	51%	1011101000001011101101011000000010101111101001101
50  	8,56%	24	26	48%	10001010111101010000111100001011101001001101010100
51  	82,86%	19	32	37%	111010100000111000010100001101000000000100111010100
52  	87,25%	30	22	58%	1110111110101110000101100100110010111001111000111100
53  	50,18%	24	29	45%	11000000001111000100011100100011111100011001001101100
54  	10,74%	32	22	59%	100011011011111011011011010101101011010001111101000011
55  	66,79%	31	24	56%	1101010101111100001111110011011011001111110000100010100
56  	22,73%	34	22	61%	10011101000110001011011000111010110001001111111111011111
57  	91,85%	29	28	51%	111101011001001011100100100000111100101011101011000011100
58  	38,76%	25	33	43%	1011000110011101011011100001010010000110001001101000100001
59  	82,17%	33	26	56%	11101001001011011001011101110000111110010101011010001001111
60  	96,89%	32	28	53%	111111000000011110100001100000100101001101100111101110111110
61  	23,67%	29	32	48%	1001111001001011010100011011101000010111101100100100100000110
62  	69,49%	34	28	55%	11011000111101010101000001111010110110000100011010101111101110
63  	95,01%	36	27	57%	111110011001110010111101111110110101100110011110110100000001000
65  	65,71%	29	36	45%	11010100000111000101100010011010100000101101100100110100001100111
70  	64,40%	34	36	49%	1101001001101110000100101101100100001100011010011011000100111011110001
75  	19,32%	33	42	44%	100110001011100111000010001010001101000011010100001001100110110111000000111
80  	82,89%	37	43	46%	11101010000110100101110001100110110111001100000100011011010110101101000110000000
85  	9,03%	39	46	46%	1000101110010000011000100111100000001100011010101000110111000110011101011101110101000
90  	40,23%	43	47	48%	101100111000000000101110110010000100110110101001000100010111000111000111101000010110111111
95  	28,87%	48	47	51%	10100100111101001111001001010110001100000111100011111110110010010100000111010001011000111110100
100 	36,98%	53	47	53%	1010111101010101111111000101100111000011001101011100100011101100011001111110110100100100100000100110
					
AVG	53%			51%	Average for wallets > #15

Keep in mind that the fist 15 keys are not representative due to small length, so the average is  calcualted for wallets greater #15.
Additional analytics for information purposes (i did not find any patterns here): K%rng is the actual private key range point (in %%). It means where the actual private key was found in the context of total range (0% is the 1st point of the range, 100% is the last point of the range). K%rng for wallet #n is (PrivKey(n) - 2^(n-1)) / 2^(n-1) * 100%

[bounty0z]

This is the result after using Kangaroo ..

Please any one know how can I use Kangaroo ? is it bruteforcing ?
Please someone can poste just easy tuto of using it to bruteforce, and thanks

bounty0z, there was no some pattern. All the keys were random.
However, i made some analysis of all the private keys for the "opened" wallets, and can say that more likely the key has the following property:

the only pattern that I get, is after 4 privatekey ,the 5th start with 1
and always and at Hex (A,B,C,D,E,F) ,more time of F and E
but its not something the was sure to use as basic

[netlakes]

bounty0z, there was no some pattern. All the keys were random.
However, i made some analysis of all the private keys for the "opened" wallets, and can say that more likely the key has the following property:

Quantity on bit "1" in the key is 45%-55% from the total bit quantity

This means that for the wallet #64 the total quantity of "1"s in the key is from 29 to 35 with the leading first bit "1" (first bit is always "1" for all keys in the puzzle). To increase your chances youl should take 29-35 "1"s, randomly mix them with the remaining "0"s and you will receieve the key. The key consists from let's say 10 "1"s bit and 54 "0"s bit is not the key for #64, as here only 15% are "1"s and the majority are "0"s.

How did I receieve this? I had a look at all the private keys in BIN format, and found that the average quantity of "1" in all the keys is 51%, the total range is 40-60%, but the most likely is 45-55%. Please have a look at all the known private keys in BIN formmat and the calculation of "1"s and "0"s in them.

Code:

No. 	K%rng	1's	0's	%1's	Private Key in BIN
01  	100,00%	1	0	100%	1
02  	100,00%	2	0	100%	11
03  	100,00%	3	0	100%	111
04  	0,00%	1	3	25%	1000
05  	40,00%	3	2	60%	10101
06  	58,06%	3	3	50%	110001
07  	20,63%	3	4	43%	1001100
08  	76,38%	3	5	38%	11100000
09  	83,14%	6	3	67%	111010011
10  	0,59%	2	8	20%	1000000010
11  	12,90%	4	7	36%	10010000011
12  	31,07%	8	4	67%	101001111011
13  	27,37%	4	9	31%	1010001100000
14  	28,73%	5	9	36%	10100100110000
15  	63,99%	9	6	60%	110100011110011
16  	57,20%	8	8	50%	1100100100110110
17  	46,22%	11	6	65%	10111011001001111
18  	51,57%	6	12	33%	110000100000001101
19  	36,39%	12	7	63%	1010111010010011111
20  	64,66%	10	10	50%	11010010110001010101
21  	72,78%	11	10	52%	110111010010100110100
22  	43,41%	12	10	55%	1011011110010000001111
23  	33,49%	12	11	52%	10101010110111001010010
24  	72,00%	9	15	38%	110111000010101000000100
25  	97,80%	17	8	68%	1111110100101111011100101
26  	62,54%	11	15	42%	11010000000011001001101110
27  	66,82%	14	13	52%	110101011000011100001110101
28  	69,60%	14	14	50%	1101100100010110110011101000
29  	49,28%	16	13	55%	10111111000100101010100011110
30  	92,44%	16	14	53%	111101100101001100110101100100
31  	95,80%	21	10	68%	1111101010011111110011101000111
32  	44,05%	15	17	47%	10111000011000101010011000101110
33  	66,18%	16	17	48%	110101001011011001010100011011000
34  	64,53%	16	18	47%	1101001010011001011001000100011101
35  	17,07%	15	20	43%	10010101110110100100001000101110000
36  	23,36%	17	19	47%	100111011110100000100000101001111100
37  	45,89%	22	15	59%	1011101010111011101010110101010010011
38  	6,94%	17	21	45%	10001000111000001011111010110011010000
39  	17,77%	20	19	51%	100101101011111100000110000001111101001
40  	82,56%	22	18	55%	1110100110101110010010010011001111010110
41  	32,63%	21	20	51%	10101001110000110100110101100110001011011
42  	31,67%	19	23	45%	101010001000100001110001011000110110001111
43  	68,48%	24	19	56%	1101011110100111011001001111100010110010001
44  	75,13%	22	22	50%	11100000001010110011010110100011010110001111
45  	13,67%	19	26	42%	100100010111111001010000101000011110000000101
46  	46,11%	19	27	41%	1011101100000110000011100010001101010101000100
47  	70,06%	24	23	51%	11011001101011000010000101101010011110010111010
48  	35,86%	31	17	65%	101011011110011011010111110011100011101110011011
49  	45,35%	25	24	51%	1011101000001011101101011000000010101111101001101
50  	8,56%	24	26	48%	10001010111101010000111100001011101001001101010100
51  	82,86%	19	32	37%	111010100000111000010100001101000000000100111010100
52  	87,25%	30	22	58%	1110111110101110000101100100110010111001111000111100
53  	50,18%	24	29	45%	11000000001111000100011100100011111100011001001101100
54  	10,74%	32	22	59%	100011011011111011011011010101101011010001111101000011
55  	66,79%	31	24	56%	1101010101111100001111110011011011001111110000100010100
56  	22,73%	34	22	61%	10011101000110001011011000111010110001001111111111011111
57  	91,85%	29	28	51%	111101011001001011100100100000111100101011101011000011100
58  	38,76%	25	33	43%	1011000110011101011011100001010010000110001001101000100001
59  	82,17%	33	26	56%	11101001001011011001011101110000111110010101011010001001111
60  	96,89%	32	28	53%	111111000000011110100001100000100101001101100111101110111110
61  	23,67%	29	32	48%	1001111001001011010100011011101000010111101100100100100000110
62  	69,49%	34	28	55%	11011000111101010101000001111010110110000100011010101111101110
63  	95,01%	36	27	57%	111110011001110010111101111110110101100110011110110100000001000
65  	65,71%	29	36	45%	11010100000111000101100010011010100000101101100100110100001100111
70  	64,40%	34	36	49%	1101001001101110000100101101100100001100011010011011000100111011110001
75  	19,32%	33	42	44%	100110001011100111000010001010001101000011010100001001100110110111000000111
80  	82,89%	37	43	46%	11101010000110100101110001100110110111001100000100011011010110101101000110000000
85  	9,03%	39	46	46%	1000101110010000011000100111100000001100011010101000110111000110011101011101110101000
90  	40,23%	43	47	48%	101100111000000000101110110010000100110110101001000100010111000111000111101000010110111111
95  	28,87%	48	47	51%	10100100111101001111001001010110001100000111100011111110110010010100000111010001011000111110100
100 	36,98%	53	47	53%	1010111101010101111111000101100111000011001101011100100011101100011001111110110100100100100000100110
					
AVG	53%			51%	Average for wallets > #15

Keep in mind that the fist 15 keys are not representative due to small length, so the average is  calcualted for wallets greater #15.
Additional analytics for information purposes (i did not find any patterns here): K%rng is the actual private key range point (in %%). It means where the actual private key was found in the context of total range (0% is the 1st point of the range, 100% is the last point of the range). K%rng for wallet #n is (PrivKey(n) - 2^(n-1)) / 2^(n-1) * 100%

Cool!


I made a php script to generate these results



b848af95c31c7000 - 33
b479223fc70f9800 - 33
a51b778c1dfa9800 - 35
cb5da3803496e000 - 31
8565165d73359800 - 31
ad9aa9f1d9c8d800 - 32
eae9d06a0dda3800 - 31
fc8699e06b942800 - 33
a87bcad3cafd3000 - 35
8b1d03767b88a800 - 30
fee40c87ff868000 - 31
9220d796b49bf000 - 32
9cc62606451f3000 - 29
b434b1ce9248f800 - 30
df1f7444b94e1000 - 34
fce5d65a4292f800 - 33
b642d85cb2fc2000 - 32
ac41754b49cb7800 - 32
bab931fe60882800 - 29
b7460cbcef883800 - 33
974fec034a650000 - 33
c6e327436c5e2000 - 31
e296a30a15cb6000 - 32
e9a6e8e8e14aa800 - 35
e369e4cce3a34800 - 35
886a4d6f9e9da000 - 35
da38c5fbc6962000 - 34
935afac54cff3000 - 35
f888618436e3f000 - 31
f3765981ce08f000 - 35
f6e9901d68c6a000 - 33
acb846ffc364a800 - 34
d0c4871bc5f30800 - 31
808784ef692fa000 - 33
8e4f264b62afe800 - 35
c7c80bdf8662d800 - 35
f9e2c298a10a7800 - 31
b97fee8bcc381000 - 35
ecb66958f8647800 - 34
ab4c5897a1462800 - 30
8e7c489527c5b000 - 33
88bc8a4e511b9000 - 29
81b2dc63cd700000 - 29
dfad627e5a748000 - 33
ddac4c0b7c2a5800 - 33
bc11ee44dc75a000 - 31
f46cc5146107a800 - 32
9f6aceb734112000 - 34
cf729a5e068cb800 - 33
ae12f3f0b5c44800 - 34
dd04d9ccba00a800 - 29
e9c3b64ad352c000 - 34
ba1c7dbb13ab0800 - 34
c4b25d1e22e95000 - 32
b5a90a950dfd7800 - 33
ea260d7b0d521800 - 34
ecbb5827bd50a800 - 33
89de30a6ba1d4000 - 34
9bed13cbcb5c7000 - 35
dacfbbe538855800 - 35
fcd919c8fe255800 - 33
a17db402f748d800 - 33


code:

Code:

<?php
for($i=0;$i<100;$i++){
$bytes = 1 . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) . rand(0,1) ;


if(substr_count($bytes, '1') >= 29 && substr_count($bytes, '1') <= 35){
echo dechex(bindec($bytes)) . " - " . substr_count($bytes, '1') .'<br>';
}
}



?>

[iparktur]

netlakes -  I made a php script to generate these results

What to do with your script?
What good is it?
How can he help us to find new keys?

[netlakes]

This script generates a binary value according to the tips of MrFreeDragon

he puts from 29 to 35 "1´s" in binary

[bounty0z]

This script generates a binary value according to the tips of MrFreeDragon

he puts from 29 to 35 "1´s" in binary

those are intervals to search in ? because didn't really understand about 29 and 35

[netlakes]

29-35 is the amount of 1´s in a binary number.

[MrFreeDragon]

This script generates a binary value according to the tips of MrFreeDragon
he puts from 29 to 35 "1´s" in binary

But actually these tips are not very big help. Even if they are correct, the decrease in total number of combinations is not too much.

For example, for 64bit key the total range is 2^63, if we take only the keys with 29-35 quantity of "1"s , so the total combinations to test is 2^62.23 (total decrease of the range less than twice).
If we limit our range to exact 32 "1"s (32 "1"s and 32 "0"s), so the total amount of combinations will be 2^59.58 (decrease approx. by 10 times)

[netlakes]

 
understand!
But either way, all tips should be tested;)

I use bitcrack, with this tip, I can create starting points.

[mrxtraf]

bounty0z, there was no some pattern. All the keys were random.
However, i made some analysis of all the private keys for the "opened" wallets, and can say that more likely the key has the following property:

Quantity on bit "1" in the key is 45%-55% from the total bit quantity

This means that for the wallet #64 the total quantity of "1"s in the key is from 29 to 35 with the leading first bit "1" (first bit is always "1" for all keys in the puzzle). To increase your chances youl should take 29-35 "1"s, randomly mix them with the remaining "0"s and you will receieve the key. The key consists from let's say 10 "1"s bit and 54 "0"s bit is not the key for #64, as here only 15% are "1"s and the majority are "0"s.

How did I receieve this? I had a look at all the private keys in BIN format, and found that the average quantity of "1" in all the keys is 51%, the total range is 40-60%, but the most likely is 45-55%. Please have a look at all the known private keys in BIN formmat and the calculation of "1"s and "0"s in them.

Code:

No. 	K%rng	1's	0's	%1's	Private Key in BIN
01  	100,00%	1	0	100%	1
02  	100,00%	2	0	100%	11
03  	100,00%	3	0	100%	111
04  	0,00%	1	3	25%	1000
05  	40,00%	3	2	60%	10101
06  	58,06%	3	3	50%	110001
07  	20,63%	3	4	43%	1001100
08  	76,38%	3	5	38%	11100000
09  	83,14%	6	3	67%	111010011
10  	0,59%	2	8	20%	1000000010
11  	12,90%	4	7	36%	10010000011
12  	31,07%	8	4	67%	101001111011
13  	27,37%	4	9	31%	1010001100000
14  	28,73%	5	9	36%	10100100110000
15  	63,99%	9	6	60%	110100011110011
16  	57,20%	8	8	50%	1100100100110110
17  	46,22%	11	6	65%	10111011001001111
18  	51,57%	6	12	33%	110000100000001101
19  	36,39%	12	7	63%	1010111010010011111
20  	64,66%	10	10	50%	11010010110001010101
21  	72,78%	11	10	52%	110111010010100110100
22  	43,41%	12	10	55%	1011011110010000001111
23  	33,49%	12	11	52%	10101010110111001010010
24  	72,00%	9	15	38%	110111000010101000000100
25  	97,80%	17	8	68%	1111110100101111011100101
26  	62,54%	11	15	42%	11010000000011001001101110
27  	66,82%	14	13	52%	110101011000011100001110101
28  	69,60%	14	14	50%	1101100100010110110011101000
29  	49,28%	16	13	55%	10111111000100101010100011110
30  	92,44%	16	14	53%	111101100101001100110101100100
31  	95,80%	21	10	68%	1111101010011111110011101000111
32  	44,05%	15	17	47%	10111000011000101010011000101110
33  	66,18%	16	17	48%	110101001011011001010100011011000
34  	64,53%	16	18	47%	1101001010011001011001000100011101
35  	17,07%	15	20	43%	10010101110110100100001000101110000
36  	23,36%	17	19	47%	100111011110100000100000101001111100
37  	45,89%	22	15	59%	1011101010111011101010110101010010011
38  	6,94%	17	21	45%	10001000111000001011111010110011010000
39  	17,77%	20	19	51%	100101101011111100000110000001111101001
40  	82,56%	22	18	55%	1110100110101110010010010011001111010110
41  	32,63%	21	20	51%	10101001110000110100110101100110001011011
42  	31,67%	19	23	45%	101010001000100001110001011000110110001111
43  	68,48%	24	19	56%	1101011110100111011001001111100010110010001
44  	75,13%	22	22	50%	11100000001010110011010110100011010110001111
45  	13,67%	19	26	42%	100100010111111001010000101000011110000000101
46  	46,11%	19	27	41%	1011101100000110000011100010001101010101000100
47  	70,06%	24	23	51%	11011001101011000010000101101010011110010111010
48  	35,86%	31	17	65%	101011011110011011010111110011100011101110011011
49  	45,35%	25	24	51%	1011101000001011101101011000000010101111101001101
50  	8,56%	24	26	48%	10001010111101010000111100001011101001001101010100
51  	82,86%	19	32	37%	111010100000111000010100001101000000000100111010100
52  	87,25%	30	22	58%	1110111110101110000101100100110010111001111000111100
53  	50,18%	24	29	45%	11000000001111000100011100100011111100011001001101100
54  	10,74%	32	22	59%	100011011011111011011011010101101011010001111101000011
55  	66,79%	31	24	56%	1101010101111100001111110011011011001111110000100010100
56  	22,73%	34	22	61%	10011101000110001011011000111010110001001111111111011111
57  	91,85%	29	28	51%	111101011001001011100100100000111100101011101011000011100
58  	38,76%	25	33	43%	1011000110011101011011100001010010000110001001101000100001
59  	82,17%	33	26	56%	11101001001011011001011101110000111110010101011010001001111
60  	96,89%	32	28	53%	111111000000011110100001100000100101001101100111101110111110
61  	23,67%	29	32	48%	1001111001001011010100011011101000010111101100100100100000110
62  	69,49%	34	28	55%	11011000111101010101000001111010110110000100011010101111101110
63  	95,01%	36	27	57%	111110011001110010111101111110110101100110011110110100000001000
65  	65,71%	29	36	45%	11010100000111000101100010011010100000101101100100110100001100111
70  	64,40%	34	36	49%	1101001001101110000100101101100100001100011010011011000100111011110001
75  	19,32%	33	42	44%	100110001011100111000010001010001101000011010100001001100110110111000000111
80  	82,89%	37	43	46%	11101010000110100101110001100110110111001100000100011011010110101101000110000000
85  	9,03%	39	46	46%	1000101110010000011000100111100000001100011010101000110111000110011101011101110101000
90  	40,23%	43	47	48%	101100111000000000101110110010000100110110101001000100010111000111000111101000010110111111
95  	28,87%	48	47	51%	10100100111101001111001001010110001100000111100011111110110010010100000111010001011000111110100
100 	36,98%	53	47	53%	1010111101010101111111000101100111000011001101011100100011101100011001111110110100100100100000100110
					
AVG	53%			51%	Average for wallets > #15

Keep in mind that the fist 15 keys are not representative due to small length, so the average is  calcualted for wallets greater #15.
Additional analytics for information purposes (i did not find any patterns here): K%rng is the actual private key range point (in %%). It means where the actual private key was found in the context of total range (0% is the 1st point of the range, 100% is the last point of the range). K%rng for wallet #n is (PrivKey(n) - 2^(n-1)) / 2^(n-1) * 100%

And what is the difference between the probability of setting a bit to 0 from 1? The probability is the same.
In this regard, the central reference point should be 50%. And the range should evenly expand into the wallpaper side. That is, 49-51, 48-52, 49-53, etc.

Quantity on bit "1" in the key is 45%-55% from the total bit quantity

Why is 45% -55%? If you take the data from the table excluding the first ten keys. Then we get a minimum value of 31% and a maximum of 68%. The difference is from 50%, 19 and 18, respectively. We take the maximum 19, 50-19 = 31, 50 + 19 = 69. That is, the search difference will be in the range of 31% -69% of the bits set to 1 or 0.

Well, in general, the right thought.

I already wrote above. You can also calculate the maximum duration of the same bits. And also use this parameter in the calculations.

By the way, the same algorithm with keys in hexadecimal representation.