Monero-Black-Marble-Flood code and paper

Monero-Black-Marble-Flood/code/block-size.R

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+
+
+n.workers <- min(floor(parallelly::availableCores()/2), 32L)
+
+future::plan(future::multicore(workers = n.workers))
+
+system.time({
+  block.data <- future.apply::future_lapply(sort(unlist(block.heights)), function(height) {
+
+    block.data <- xmr.rpc(url.rpc = paste0(url.rpc, "/json_rpc"),
+      method = "get_block",
+      params = list(height = height ),
+      keep.trying.rpc = TRUE)$result
+
+    as.data.frame(block.data$block_header)
+
+  })
+})
+
+
+block.data <- rbindlist(block.data)
+
+block.data[, timestamp.POSIX := as.POSIXct(timestamp)]
+
+
+block.data[, block_weight.rolling.max := zoo::rollapply(block.data$block_weight, width = 30, FUN = max, fill = NA)]
+
+
+png("rolling-max-block-weight.png", width = 500, height = 600)
+
+ggplot(block.data[timestamp.POSIX >= as.POSIXct((start.spam.date - 5)), ], aes(x = timestamp.POSIX, y = block_weight.rolling.max / 1000)) +
+  geom_line() +
+  scale_y_continuous(limit = c(0, NA), expand = c(0, 0)) +
+  scale_x_datetime(date_breaks = "day", expand = c(0, 0), guide = guide_axis(angle = 90)) +
+  ggtitle("Monero empirical block weight (maximum peaks)",
+    subtitle = "To smooth the line, the 30 block (1 hr) rolling maximum is displayed") +
+  xlab("                                                    Date              github.com/Rucknium") +
+  ylab("Block weight in kB (bytes/10^3)")   +
+  theme(plot.title = element_text(size = 20),
+    plot.subtitle = element_text(size = 15),
+    axis.text = element_text(size = 15),
+    axis.title.x = element_text(size = 15, margin = margin(t = 10)),
+    axis.title.y = element_text(size = 15), strip.text = element_text(size = 15))
+
+dev.off()
+
+block.data[, block_weight.100.block.median := zoo::rollapply(block.data$block_weight, width = 101, FUN = median, fill = NA, align = "right")]
+
+png("rolling-median-block-weight.png", width = 500, height = 600)
+
+ggplot(block.data[timestamp.POSIX >= as.POSIXct((start.spam.date - 5)), ], aes(x = timestamp.POSIX, y = block_weight.100.block.median / 1000)) +
+  geom_line() +
+  scale_y_continuous(limit = c(0, max(block.data$block_weight.rolling.max / 1000, na.rm = TRUE)), expand = c(0, 0)) +
+  scale_x_datetime(date_breaks = "day", expand = c(0, 0), guide = guide_axis(angle = 90)) +
+  ggtitle("Monero empirical block weight",
+    subtitle = "100 block rolling median") +
+  xlab("                                                    Date              github.com/Rucknium") +
+  ylab("Block weight in kB (bytes/10^3)")   +
+  theme(plot.title = element_text(size = 20),
+    plot.subtitle = element_text(size = 15),
+    axis.text = element_text(size = 15),
+    axis.title.x = element_text(size = 15, margin = margin(t = 10)),
+    axis.title.y = element_text(size = 15), strip.text = element_text(size = 15))
+
+dev.off()
+
+

Monero-Black-Marble-Flood/code/effective-ring-size-projections.R

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+
+
+mean.coinbase.tx.size <- output.index[!duplicated(tx_hash) & tx_num == 1, mean(tx_size_bytes)]
+
+num.blocks.since.spam <- output.index[block_height >= start.spam.height, uniqueN(block_height)]
+
+mean.size.1in.2out <- spam.results[[1]]$non.spam.fingerprint.tx[number_of_inputs == 1 & number_of_outputs == 2, mean(tx_size_bytes)]
+mean.size.2in.2out <- spam.results[[1]]$non.spam.fingerprint.tx[number_of_inputs == 2 & number_of_outputs == 2, mean(tx_size_bytes)]
+mean.size.16.ring.input <- mean.size.2in.2out - mean.size.1in.2out
+
+mean.size.zero.ring.tx.size <- mean.size.1in.2out - mean.size.16.ring.input
+# This "size zero ring" is so that the variable ring size can be added later
+
+mean.size.16.ring.input <- mean.size.16.ring.input - 32
+# Subtract key image bytes since there is just one key image per ring
+mean.size.one.ring.member <- mean.size.16.ring.input / 16
+
+
+
+
+sim.spam <- lapply(c(11, 16, 25, 40, 60), FUN = function(ring.size.sim) {
+
+  non.spam.fingerprint.tx.sim <- copy(spam.results[[1]]$non.spam.fingerprint.tx)
+
+  non.spam.fingerprint.tx.sim[, tx_weight_bytes.sim :=
+      tx_weight_bytes - mean.size.16.ring.input * number_of_inputs + number_of_inputs * mean.size.one.ring.member * ring.size.sim]
+
+  mean.non.spam.kb.per.block <- mean.coinbase.tx.size/1000 +
+    (sum(non.spam.fingerprint.tx.sim[block_height >= start.spam.height, tx_weight_bytes.sim])/num.blocks.since.spam)/1000
+
+
+  mean.non.spam.output.per.block <- nrow(non.spam.fingerprint[block_height >= start.spam.height, ])/num.blocks.since.spam
+
+  mean.effective.ring.size <- ring.size.sim
+  simulated.adversary.owned.outputs <- 0
+  mean.kb.per.block <- mean.non.spam.kb.per.block
+  block.size <- mean.non.spam.kb.per.block
+
+  mean.kb.per.block.data <- vector("numeric", 100000)
+  mean.effective.ring.size.data <- vector("numeric", 100000)
+  median.effective.ring.size.data <- vector("numeric", 100000)
+  simulated.adversary.owned.share.data <-  vector("numeric", 100000)
+
+  i <- 0
+  # while (mean.effective.ring.size >= 2) {
+  while (mean.kb.per.block <= 3000) {
+    i <- i + 1
+    simulated.adversary.owned.share <- simulated.adversary.owned.outputs/(simulated.adversary.owned.outputs + mean.non.spam.output.per.block)
+    mean.effective.ring.size <- 1 + (ring.size.sim - 1) * (1 - simulated.adversary.owned.share)
+    mean.kb.per.block.data[i] <- mean.kb.per.block
+    mean.effective.ring.size.data[i] <- mean.effective.ring.size
+    median.effective.ring.size.data[i] <- 1 + qbinom(0.5, size = ring.size.sim - 1, prob = 1 - simulated.adversary.owned.share)
+    simulated.adversary.owned.share.data[i] <- simulated.adversary.owned.share
+
+    simulated.adversary.owned.outputs <- simulated.adversary.owned.outputs + 2
+    mean.kb.per.block <- mean.kb.per.block + mean.size.zero.ring.tx.size / 1000 + mean.size.one.ring.member * ring.size.sim / 1000
+    # Add adversary outputs at the end so the first iteration has zero adversary outputs
+  }
+
+  sim.spam <- data.table(mean.kb.per.block.data = mean.kb.per.block.data[seq_len(i)],
+    mean.effective.ring.size.data = mean.effective.ring.size.data[seq_len(i)],
+    median.effective.ring.size.data = median.effective.ring.size.data[seq_len(i)],
+    simulated.adversary.owned.share.data = simulated.adversary.owned.share.data[seq_len(i)],
+    ring.size.sim = ring.size.sim,
+    ring.size.sim.label = paste0(ring.size.sim, " (", round(mean.non.spam.kb.per.block), " kB non-spam)"))
+
+  sim.spam
+})
+
+sim.spam <- rbindlist(sim.spam)
+
+
+
+max.ring.size.sim <- max(sim.spam$ring.size.sim)
+
+png("projected-effective-ring-size-non-log.png", width = 600, height = 600)
+
+ggplot(sim.spam, aes(x = mean.kb.per.block.data, y = mean.effective.ring.size.data, colour = ring.size.sim.label)) +
+  geom_line() +
+  scale_y_continuous(breaks = seq(2, max.ring.size.sim, by = 2), limits = c(0, NA), expand = c(0, 0)) +
+  scale_x_continuous(breaks = seq(0, 10000, by = 500), limits = c(0, NA), expand = c(0, 0)) +
+  ggtitle("Long-term projected mean effective ring size") +
+  xlab("                  Block weight in kilobytes (10^3 bytes)     github.com/Rucknium") +
+  ylab("Effective ring size")  +
+  labs(colour = "Ring size") +
+  theme(legend.position = "top", legend.text = element_text(size = 12), legend.title = element_text(size = 15),
+    plot.title = element_text(size = 20),
+    plot.subtitle = element_text(size = 15),
+    axis.text = element_text(size = 15),
+    axis.title.x = element_text(size = 15, margin = margin(t = 10)),
+    axis.title.y = element_text(size = 15), strip.text = element_text(size = 15)) +
+  guides(colour = guide_legend(nrow = 2, byrow = FALSE, override.aes = list(linewidth = 5)))
+
+dev.off()
+
+
+
+min.mean.kb.per.block.data <- ceiling(min(sim.spam$mean.kb.per.block.data))
+
+png("projected-effective-ring-size-log-log.png", width = 600, height = 600)
+
+ggplot(sim.spam, aes(x = mean.kb.per.block.data, y = mean.effective.ring.size.data, colour = ring.size.sim.label)) +
+  geom_line() +
+  scale_y_log10(breaks = c(1, seq(2, max.ring.size.sim, by = 2)), limits = c(1, NA), expand = c(0, 0) ) +
+  scale_x_log10(breaks = c(min.mean.kb.per.block.data, seq(0, 10000, by = 250)), guide = guide_axis(angle = 90), expand = c(0, 0)) +
+  ggtitle("Long-term projected mean effective ring size (log-log scale)") +
+  xlab("       Block weight in kilobytes (10^3 bytes) (log scale)     github.com/Rucknium") +
+  ylab("Effective ring size (log scale)")  +
+  labs(colour = "Ring size") +
+  theme(legend.position = "top", legend.text = element_text(size = 12), legend.title = element_text(size = 15),
+    plot.title = element_text(size = 20),
+    plot.subtitle = element_text(size = 15),
+    axis.text = element_text(size = 15),
+    axis.title.x = element_text(size = 15, margin = margin(t = 10)),
+    axis.title.y = element_text(size = 15), strip.text = element_text(size = 15)) +
+  guides(colour = guide_legend(nrow = 2, byrow = FALSE, override.aes = list(linewidth = 5)))
+
+dev.off()
+
+
+
+
+png("projected-ring-size-one.png", width = 600, height = 600)
+
+ggplot(sim.spam, aes(x = mean.kb.per.block.data,
+  y = dbinom(0, size = ring.size.sim - 1, prob = 1 - simulated.adversary.owned.share.data),
+  colour = ring.size.sim.label)) +
+  geom_line() +
+  scale_y_continuous( limits = c(0, 1), expand = c(0, 0), labels = scales::label_percent()) +
+  scale_x_continuous(breaks = seq(0, 10000, by = 250), limits = c(0, NA), expand = c(0, 0), guide = guide_axis(angle = 90)) +
+  ggtitle("Long-term projected share of rings with effective ring size 1") +
+  xlab("       Block weight in kilobytes (10^3 bytes) (log scale)     github.com/Rucknium") +
+  ylab("Share of rings")  +
+  labs(colour = "Ring size") +
+  theme(legend.position = "top", legend.text = element_text(size = 12), legend.title = element_text(size = 15),
+    plot.title = element_text(size = 20),
+    plot.subtitle = element_text(size = 15),
+    axis.text = element_text(size = 15),
+    axis.title.x = element_text(size = 15, margin = margin(t = 10)),
+    axis.title.y = element_text(size = 15), strip.text = element_text(size = 15)) +
+  guides(colour = guide_legend(nrow = 2, byrow = FALSE, override.aes = list(linewidth = 5)))
+
+dev.off()
+
+
+
+
+
+