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5b4fea72cf
Co-authored-by: plowsof <plowsof@protonmail.com> extra files
75 lines
2.4 KiB
Python
Executable File
75 lines
2.4 KiB
Python
Executable File
#!/usr/bin/env python
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# Simulate a maximal block attack on the Monero network
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# This uses the scheme proposed by ArticMine
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# Written by Sarang Nother
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# Copyright (c) 2019-2023, The Monero Project
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from __future__ import print_function
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import sys
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import math
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MEDIAN_WINDOW_SMALL = 100 # number of recent blocks for median computation
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MEDIAN_WINDOW_BIG = 5000
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MULTIPLIER_BIG = 50.0
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MEDIAN_THRESHOLD = 300*1000 # initial value for median (scaled kB -> B)
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lcg_seed = 0
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embw = MEDIAN_THRESHOLD
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ltembw = MEDIAN_THRESHOLD
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weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_SMALL # weights of recent blocks (B), with index -1 most recent
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lt_weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_BIG # long-term weights
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# Compute the median of a list
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def get_median(vec):
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#temp = vec
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temp = sorted(vec)
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if len(temp) % 2 == 1:
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return temp[len(temp)//2]
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else:
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return int((temp[len(temp)//2]+temp[len(temp)//2-1])//2)
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def LCG():
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global lcg_seed
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lcg_seed = (lcg_seed * 0x100000001b3 + 0xcbf29ce484222325) & 0xffffffff
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return lcg_seed
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def run(t, blocks):
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global embw
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global ltembw
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weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_SMALL # weights of recent blocks (B), with index -1 most recent
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lt_weights = [MEDIAN_THRESHOLD]*MEDIAN_WINDOW_BIG # long-term weights
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for block in range(blocks):
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# determine the long-term effective weight
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ltmedian = get_median(lt_weights[-MEDIAN_WINDOW_BIG:])
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ltembw = max(MEDIAN_THRESHOLD,ltmedian)
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# determine the effective weight
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stmedian = get_median(weights[-MEDIAN_WINDOW_SMALL:])
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embw = min(max(MEDIAN_THRESHOLD,stmedian),int(MULTIPLIER_BIG*ltembw))
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# drop the lowest values
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weights = weights[1:]
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lt_weights = lt_weights[1:]
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# add a block of max weight
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if t == 0:
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max_weight = 2 * embw
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elif t == 1:
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r = LCG()
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max_weight = int(90 + r % 500000 + 250000 + math.sin(block / 200.) * 350000)
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if max_weight < 90: max_weight = 90
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elif t == 2:
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max_weight = 90
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else:
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sys.exit(1)
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weights.append(max_weight)
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lt_weights.append(min(max_weight,int(ltembw + int(ltembw * 2 / 5))))
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#print "H %u, r %u, BW %u, EMBW %u, LTBW %u, LTEMBW %u, ltmedian %u" % (block, r, max_weight, embw, lt_weights[-1], ltembw, ltmedian)
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print("H %u, BW %u, EMBW %u, LTBW %u" % (block, max_weight, embw, lt_weights[-1]))
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run(0, 2 * MEDIAN_WINDOW_BIG)
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run(1, 9 * MEDIAN_WINDOW_BIG)
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run(2, 1 * MEDIAN_WINDOW_BIG)
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