Git-Mirrors/monero
1
0
Fork 0
mirror of https://github.com/monero-project/monero.git synced 2024-12-26 12:49:27 -05:00
Code Issues Packages Projects Releases Wiki Activity

fix typos (@hinto-janai)

Browse Source
This commit is contained in:
jeffro256 2023-12-13 13:29:15 -06:00
parent 9103f008f6
commit 813ad56b4a
No known key found for this signature in database
GPG Key ID: 6F79797A6E392442
2 changed files with 15 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
docs/DECOY_SELECTION.md
View File

@ -32,8 +32,8 @@ contain ring members with the same amount.
Finally, when we are doing decoy selection to find the other members of a ring, our result is a list of global output Finally, when we are doing decoy selection to find the other members of a ring, our result is a list of global output
indexes, which represent a set of transaction outputs with the same amount as the transaction output we are trying to indexes, which represent a set of transaction outputs with the same amount as the transaction output we are trying to
spend. We sample these global output indicies according to a certain distribution, with this distribution hopefully spend. We sample these global output indices according to a certain distribution, with this distribution hopefully
statistically matching the distribution of the ages of "true spends", so that the ring member we truely wish to spend is statistically matching the distribution of the ages of "true spends", so that the ring member we truly wish to spend is
masked from external observers within a certain probability. masked from external observers within a certain probability.
### How Transaction Unlock Times Affect Decoy Selection ### How Transaction Unlock Times Affect Decoy Selection
@ -53,7 +53,7 @@ unusable. It then picks from the valid remaining outputs. The trap that one can
statistical dependence for picks within rings more than necessary. When you are trying to build up a set of X unique statistical dependence for picks within rings more than necessary. When you are trying to build up a set of X unique
decoy picks, if the first pick has 100 choices, then the next pick has 99 choices, then 98 choices, etc, etc. Since decoy picks, if the first pick has 100 choices, then the next pick has 99 choices, then 98 choices, etc, etc. Since
these picks are not statistically independent, then the distribution of the picks gets more and more skewed for the later these picks are not statistically independent, then the distribution of the picks gets more and more skewed for the later
picks. You can combat this effect by simply commiting to the order in which you pick the outputs, and try adding them picks. You can combat this effect by simply committing to the order in which you pick the outputs, and try adding them
in this order, assuming that they are valid. in this order, assuming that they are valid.
## Implementing Decoy Selection ## Implementing Decoy Selection
@ -69,9 +69,9 @@ and methods.
### First, Some Numeric Constants ### First, Some Numeric Constants
* `GAMMA_SHAPE = 19.28` [source](https://github.com/monero-project/monero/blob/67d190ce7c33602b6a3b804f633ee1ddb7fbb4a1/src/wallet/wallet2.cpp#L141-L142) * `GAMMA_SHAPE = 19.28` [source](https://github.com/monero-project/monero/blob/67d190ce7c33602b6a3b804f633ee1ddb7fbb4a1/src/wallet/wallet2.cpp#L141-L142)
* Shape paramater for a [gamma distribution](https://en.wikipedia.org/wiki/Gamma_distribution) * Shape parameter for a [gamma distribution](https://en.wikipedia.org/wiki/Gamma_distribution)
* `GAMMA_RATE = 1.61` [source](https://github.com/monero-project/monero/blob/67d190ce7c33602b6a3b804f633ee1ddb7fbb4a1/src/wallet/wallet2.cpp#L141-L142) * `GAMMA_RATE = 1.61` [source](https://github.com/monero-project/monero/blob/67d190ce7c33602b6a3b804f633ee1ddb7fbb4a1/src/wallet/wallet2.cpp#L141-L142)
* Rate paramater for a [gamma distribution](https://en.wikipedia.org/wiki/Gamma_distribution) * Rate parameter for a [gamma distribution](https://en.wikipedia.org/wiki/Gamma_distribution)
* :memo: **NOTE**: Here we used a "rate" parameter, but gamma distributions can also be parameterized with a "scale" parameter, where `scale = 1 / rate`. If you use a library to sample from a gamma distribution, make sure you don't get rate & scale mixed up. * :memo: **NOTE**: Here we used a "rate" parameter, but gamma distributions can also be parameterized with a "scale" parameter, where `scale = 1 / rate`. If you use a library to sample from a gamma distribution, make sure you don't get rate & scale mixed up.
* `DIFFICULTY_TARGET_V2 = 120` [source](https://github.com/monero-project/monero/blob/67d190ce7c33602b6a3b804f633ee1ddb7fbb4a1/src/cryptonote_config.h#L79) * `DIFFICULTY_TARGET_V2 = 120` [source](https://github.com/monero-project/monero/blob/67d190ce7c33602b6a3b804f633ee1ddb7fbb4a1/src/cryptonote_config.h#L79)
* The current protocol target blocktime, in seconds * The current protocol target blocktime, in seconds
@ -230,10 +230,10 @@ until we have built up a set of global output indices of a certain desired size.
* `target_num_outputs_post_unlock = floor(target_post_unlock_output_age / average_output_delay)` * `target_num_outputs_post_unlock = floor(target_post_unlock_output_age / average_output_delay)`
5. Here is the first point in which a gamma pick can fail: if the target output index post-unlock is greater than the number of usable outputs on chain: 5. Here is the first point in which a gamma pick can fail: if the target output index post-unlock is greater than the number of usable outputs on chain:
* If `target_num_outputs_post_unlock >= num_usable_rct_outputs`, then restart the gamma pick operation from step 1. * If `target_num_outputs_post_unlock >= num_usable_rct_outputs`, then restart the gamma pick operation from step 1.
6. Now we get what I call a "psuedo global output index". This value *could* be used as a global output index, but since we want all outputs within the same block to have the same chance of being picked, we instead use this global output index to "pick" a block. 6. Now we get what I call a "pseudo global output index". This value *could* be used as a global output index, but since we want all outputs within the same block to have the same chance of being picked, we instead use this global output index to "pick" a block.
* `psuedo_global_output_index = num_usable_rct_outputs - 1 - target_num_outputs_post_unlock` * `pseudo_global_output_index = num_usable_rct_outputs - 1 - target_num_outputs_post_unlock`
7. Let us get the block index containing our psuedo global output index. In practice, one can use a binary search to perform this operation in `O(log(CROD_length))` time. 7. Let us get the block index containing our pseudo global output index. In practice, one can use a binary search to perform this operation in `O(log(CROD_length))` time.
* `picked_block_index = i such that CROD[i] <= psuedo_global_output_index < CROD[i + 1]` * `picked_block_index = i such that CROD[i] <= pseudo_global_output_index < CROD[i + 1]`
8. To pick an output from this block, we need the first global output index in this block. 8. To pick an output from this block, we need the first global output index in this block.
* If `picked_block_index == 0`, then `block_first_global_output_index = 0`, else `block_first_global_output_index = CROD[picked_block_index - 1]` * If `picked_block_index == 0`, then `block_first_global_output_index = 0`, else `block_first_global_output_index = CROD[picked_block_index - 1]`
9. From this block, we also need to know how many outputs are contained within: 9. From this block, we also need to know how many outputs are contained within:
@ -283,10 +283,10 @@ def gamma_pick(crod, average_output_delay, num_usable_rct_outputs):
continue continue
# 6 # 6
psuedo_global_output_index = num_usable_rct_outputs - 1 - target_num_outputs_post_unlock pseudo_global_output_index = num_usable_rct_outputs - 1 - target_num_outputs_post_unlock
# 7 # 7
picked_block_index = bisect.bisect_left(crod, psuedo_global_output_index) picked_block_index = bisect.bisect_left(crod, pseudo_global_output_index)
# 8 # 8
if picked_block_index == 0: if picked_block_index == 0:
@ -313,7 +313,7 @@ Assuming that we can correctly treat the distribution of picks by the decoy sele
distribution, we can use a two-sample [Kolmogorov–Smirnov Test](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test) distribution, we can use a two-sample [Kolmogorov–Smirnov Test](https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test)
to statistically test if a given implementation statistically matches the reference implementation. Running the provided to statistically test if a given implementation statistically matches the reference implementation. Running the provided
Python decoy selection reference script (utils/python-rpc/decoy_selection.py) will generate a TXT file containing Python decoy selection reference script (utils/python-rpc/decoy_selection.py) will generate a TXT file containing
decoy selection picks (you can specify how many) seperated by newlines. This data can be imported and used to perform decoy selection picks (you can specify how many) separated by newlines. This data can be imported and used to perform
a two-sample KS test using, for example, `scipy.stats.kstest`. Just make sure that when you're testing, you use the same a two-sample KS test using, for example, `scipy.stats.kstest`. Just make sure that when you're testing, you use the same
*CROD* list, which can be enforced in the Python script with the argument `--to-height`. *CROD* list, which can be enforced in the Python script with the argument `--to-height`.

6
utils/python-rpc/decoy_selection.py
View File

@ -78,10 +78,10 @@ def gamma_pick(crod, average_output_delay, num_usable_rct_outputs):
continue continue
# 6 # 6
psuedo_global_output_index = num_usable_rct_outputs - 1 - target_num_outputs_post_unlock pseudo_global_output_index = num_usable_rct_outputs - 1 - target_num_outputs_post_unlock
# 7 # 7
picked_block_index = bisect.bisect_left(crod, psuedo_global_output_index) picked_block_index = bisect.bisect_left(crod, pseudo_global_output_index)
# 8 # 8
if picked_block_index == 0: if picked_block_index == 0:
@ -104,7 +104,7 @@ def gamma_pick(crod, average_output_delay, num_usable_rct_outputs):
def main(): def main():
# Handle CLI arguments # Handle CLI arguments
arg_parser = argparse.ArgumentParser(prog='Decoy Selection Python Reference', arg_parser = argparse.ArgumentParser(prog='Decoy Selection Python Reference',
description='We provide an easy-to-read non-fingerprinting reference for Monero decoy selecton', description='We provide an easy-to-read non-fingerprinting reference for Monero decoy selection',
epilog='Remember: Don\'t be Unique!') epilog='Remember: Don\'t be Unique!')
arg_parser.add_argument('-t', '--to-height', default=0, type=int) arg_parser.add_argument('-t', '--to-height', default=0, type=int)
arg_parser.add_argument('-n', '--num-picks', default=1000000, type=int) arg_parser.add_argument('-n', '--num-picks', default=1000000, type=int)