[tor-commits] [torflow/master] Clarify that trials are circuit counts in output.
mikeperry at torproject.org
mikeperry at torproject.org
Thu Oct 11 01:57:34 UTC 2012
commit 04ed8e5dc3b357f6d7c012b6192f7c841b04aaed
Author: Mike Perry <mikeperry-git at fscked.org>
Date: Wed Oct 10 18:56:22 2012 -0700
Clarify that trials are circuit counts in output.
---
CircuitAnalysis/PathBias/path_bias.py | 48 ++++++------
CircuitAnalysis/PathBias/results.txt | 145 +++++++++++++++++----------------
2 files changed, 97 insertions(+), 96 deletions(-)
diff --git a/CircuitAnalysis/PathBias/path_bias.py b/CircuitAnalysis/PathBias/path_bias.py
index 54e8581..f3fc1bd 100755
--- a/CircuitAnalysis/PathBias/path_bias.py
+++ b/CircuitAnalysis/PathBias/path_bias.py
@@ -517,68 +517,68 @@ def main():
if True:
print "\n\n===================== False Positives ============================"
- print "\nStartup false positive counts at [trials, success_rate, min_circs, path_bias_pct]:"
+ print "\nStartup false positive counts at [num_circs, success_rate, min_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs min_circs)"
print brute_force(lambda x,y: x<y,
startup_false_positive_test,
- #false_positive_test(trials, success_rate, min_circs, path_bias_pct):
- [(100000,100000), (0.80, 0.80), (20,200), (70, 70)],
- [0, -0.1, 20, 5])
+ #false_positive_test(num_circs, success_rate, min_circs, path_bias_pct):
+ [(1000000,1000000), (0.80, 0.80), (25,250), (70, 70)],
+ [0, -0.1, 25, 5])
- print "\nStartup false positive counts at [trials, success_rate, min_circs, path_bias_pct]:"
+ print "\nStartup false positive counts at [num_circs, success_rate, min_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs min_circs)"
print brute_force(lambda x,y: x<y,
startup_false_positive_test,
- #false_positive_test(trials, success_rate, min_circs, path_bias_pct):
- [(100000,100000), (0.45, 0.45), (20,200), (30, 30)],
- [0, -0.1, 20, 5])
+ #false_positive_test(num_circs, success_rate, min_circs, path_bias_pct):
+ [(1000000,1000000), (0.45, 0.45), (25,250), (30, 30)],
+ [0, -0.1, 25, 5])
- print "\nFalse positive counts at [trials, success_rate, scale_circs, path_bias_pct]:"
+ print "\nFalse positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs scale_circs)"
print brute_force(lambda x,y: x<y,
reject_false_positive_test,
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(1000000,1000000), (0.70, 0.70), (100,500), (70, 70)],
[0, -0.1, 50, 5])
- print "\nFalse positive counts at [trials, success_rate, scale_circs, path_bias_pct]:"
+ print "\nFalse positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs scale_circs)"
print brute_force(lambda x,y: x<y,
reject_false_positive_test,
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(1000000,1000000), (0.75, 0.75), (100,500), (70, 70)],
[0, -0.1, 50, 5])
- print "\nFalse positive counts at [trials, success_rate, scale_circs, path_bias_pct]:"
+ print "\nFalse positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs scale_circs)"
print brute_force(lambda x,y: x<y,
reject_false_positive_test,
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(1000000,1000000), (0.80, 0.80), (100,500), (70, 70)],
[0, -0.1, 50, 5])
- print "\nFalse positive counts at [trials, success_rate, scale_circs, path_bias_pct]:"
+ print "\nFalse positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs scale_circs)"
print brute_force(lambda x,y: x<y,
reject_false_positive_test,
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(1000000,1000000), (0.55, 0.55), (100,500), (50, 50)],
[0, -0.1, 50, 5])
- print "\nFalse positive counts at [trials, success_rate, scale_circs, path_bias_pct]:"
+ print "\nFalse positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs scale_circs)"
print brute_force(lambda x,y: x<y,
reject_false_positive_test,
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(1000000,1000000), (0.60, 0.60), (100,500), (50, 50)],
[0, -0.1, 50, 5])
- print "\nFalse positive counts at [trials, success_rate, scale_circs, path_bias_pct]:"
+ print "\nFalse positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:"
print "(Results are some function of success_rate - path_bias_pct vs scale_circs)"
print brute_force(lambda x,y: x<y,
reject_false_positive_test,
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(1000000,1000000), (0.45, 0.45), (100,500), (30, 30)],
[0, -0.1, 50, 5])
@@ -587,16 +587,16 @@ def main():
print "\nDoS attack durations (in circs) at [success_rate, dos_success_rate, path_bias_pct, scale_thresh]:"
print brute_force(lambda x,y: x>y,
dos_attack_test,
- #dos_attack_test(g, trials, success_rate, dos_success_rate, path_bias_pct):
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #dos_attack_test(g, num_circs, success_rate, dos_success_rate, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(0.80, 0.80), (0.05,0.05), (30, 30), (200, 1000)],
[-0.1, -0.1, 5, 100])
print "\nDoS attack durations (in circs) at [success_rate, dos_success_rate, path_bias_pct, scale_thresh]:"
print brute_force(lambda x,y: x<y,
dos_attack_test,
- #dos_attack_test(g, trials, success_rate, dos_success_rate, path_bias_pct):
- #false_positive_test(trials, success_rate, scale_circs, path_bias_pct):
+ #dos_attack_test(g, num_circs, success_rate, dos_success_rate, path_bias_pct):
+ #false_positive_test(num_circs, success_rate, scale_circs, path_bias_pct):
[(0.80, 0.80), (0.25,0.05), (30, 30), (500, 500)],
[-0.1, -0.1, 5, 100])
diff --git a/CircuitAnalysis/PathBias/results.txt b/CircuitAnalysis/PathBias/results.txt
index d8e1c97..094b495 100644
--- a/CircuitAnalysis/PathBias/results.txt
+++ b/CircuitAnalysis/PathBias/results.txt
@@ -81,87 +81,88 @@ New extrema at [100000, 0.75, 0.8500000000000001, 50]: 85085.0
===================== False Positives ============================
-Startup false positive counts at [trials, success_rate, min_circs, path_bias_pct]:
+Startup false positive counts at [num_circs, success_rate, min_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs min_circs)
-New extrema at [100000, 0.8, 20, 70]: 1423
-New extrema at [100000, 0.8, 40, 70]: 301
-New extrema at [100000, 0.8, 60, 70]: 93
-New extrema at [100000, 0.8, 80, 70]: 38
-New extrema at [100000, 0.8, 100, 70]: 18
-New extrema at [100000, 0.8, 120, 70]: 5
-New extrema at [100000, 0.8, 160, 70]: 1
-New extrema at [100000, 0.8, 180, 70]: 0
-[100000, 0.8, 200, 70]
-
-Startup false positive counts at [trials, success_rate, min_circs, path_bias_pct]:
+New extrema at [1000000, 0.8, 25, 70]: 9704
+New extrema at [1000000, 0.8, 50, 70]: 1571
+New extrema at [1000000, 0.8, 75, 70]: 469
+New extrema at [1000000, 0.8, 100, 70]: 143
+New extrema at [1000000, 0.8, 125, 70]: 54
+New extrema at [1000000, 0.8, 150, 70]: 31
+New extrema at [1000000, 0.8, 175, 70]: 6
+New extrema at [1000000, 0.8, 225, 70]: 3
+New extrema at [1000000, 0.8, 250, 70]: 0
+[1000000, 0.8, 250, 70]
+
+Startup false positive counts at [num_circs, success_rate, min_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs min_circs)
-New extrema at [100000, 0.45, 20, 30]: 811
-New extrema at [100000, 0.45, 40, 30]: 123
-New extrema at [100000, 0.45, 60, 30]: 25
-New extrema at [100000, 0.45, 80, 30]: 3
-New extrema at [100000, 0.45, 100, 30]: 0
-[100000, 0.45, 200, 30]
-
-False positive counts at [trials, success_rate, scale_circs, path_bias_pct]:
+New extrema at [1000000, 0.45, 25, 30]: 4893
+New extrema at [1000000, 0.45, 50, 30]: 497
+New extrema at [1000000, 0.45, 75, 30]: 96
+New extrema at [1000000, 0.45, 100, 30]: 15
+New extrema at [1000000, 0.45, 125, 30]: 8
+New extrema at [1000000, 0.45, 150, 30]: 2
+New extrema at [1000000, 0.45, 175, 30]: 0
+[1000000, 0.45, 250, 30]
+
+False positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs scale_circs)
-New extrema at [1000000, 0.7, 100, 70]: 17156
-New extrema at [1000000, 0.7, 150, 70]: 13887
-New extrema at [1000000, 0.7, 200, 70]: 12295
-New extrema at [1000000, 0.7, 250, 70]: 11436
-New extrema at [1000000, 0.7, 300, 70]: 10390
-New extrema at [1000000, 0.7, 350, 70]: 9703
-New extrema at [1000000, 0.7, 400, 70]: 8697
-New extrema at [1000000, 0.7, 500, 70]: 8271
+New extrema at [1000000, 0.7, 100, 70]: 16805
+New extrema at [1000000, 0.7, 150, 70]: 13963
+New extrema at [1000000, 0.7, 200, 70]: 11911
+New extrema at [1000000, 0.7, 250, 70]: 11067
+New extrema at [1000000, 0.7, 300, 70]: 10310
+New extrema at [1000000, 0.7, 350, 70]: 9828
+New extrema at [1000000, 0.7, 400, 70]: 9273
+New extrema at [1000000, 0.7, 450, 70]: 8294
[1000000, 0.7, 500, 70]
-False positive counts at [trials, success_rate, scale_circs, path_bias_pct]:
+False positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs scale_circs)
-New extrema at [1000000, 0.75, 100, 70]: 3679
-New extrema at [1000000, 0.75, 150, 70]: 1826
-New extrema at [1000000, 0.75, 200, 70]: 1134
-New extrema at [1000000, 0.75, 250, 70]: 577
-New extrema at [1000000, 0.75, 300, 70]: 365
-New extrema at [1000000, 0.75, 350, 70]: 228
-New extrema at [1000000, 0.75, 400, 70]: 117
-New extrema at [1000000, 0.75, 450, 70]: 77
+New extrema at [1000000, 0.75, 100, 70]: 3554
+New extrema at [1000000, 0.75, 150, 70]: 1833
+New extrema at [1000000, 0.75, 200, 70]: 1126
+New extrema at [1000000, 0.75, 250, 70]: 544
+New extrema at [1000000, 0.75, 300, 70]: 412
+New extrema at [1000000, 0.75, 350, 70]: 237
+New extrema at [1000000, 0.75, 400, 70]: 132
+New extrema at [1000000, 0.75, 450, 70]: 54
+New extrema at [1000000, 0.75, 500, 70]: 33
[1000000, 0.75, 500, 70]
-False positive counts at [trials, success_rate, scale_circs, path_bias_pct]:
+False positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs scale_circs)
-New extrema at [1000000, 0.8, 100, 70]: 123
-New extrema at [1000000, 0.8, 150, 70]: 29
-New extrema at [1000000, 0.8, 200, 70]: 9
-New extrema at [1000000, 0.8, 250, 70]: 3
-New extrema at [1000000, 0.8, 300, 70]: 0
+New extrema at [1000000, 0.8, 100, 70]: 147
+New extrema at [1000000, 0.8, 150, 70]: 17
+New extrema at [1000000, 0.8, 200, 70]: 2
+New extrema at [1000000, 0.8, 250, 70]: 0
[1000000, 0.8, 500, 70]
-False positive counts at [trials, success_rate, scale_circs, path_bias_pct]:
+False positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs scale_circs)
-New extrema at [1000000, 0.55, 100, 50]: 4739
-New extrema at [1000000, 0.55, 150, 50]: 2754
-New extrema at [1000000, 0.55, 200, 50]: 1618
-New extrema at [1000000, 0.55, 250, 50]: 1123
-New extrema at [1000000, 0.55, 300, 50]: 682
-New extrema at [1000000, 0.55, 350, 50]: 326
-New extrema at [1000000, 0.55, 400, 50]: 322
-New extrema at [1000000, 0.55, 450, 50]: 189
-New extrema at [1000000, 0.55, 500, 50]: 152
+New extrema at [1000000, 0.55, 100, 50]: 4878
+New extrema at [1000000, 0.55, 150, 50]: 2765
+New extrema at [1000000, 0.55, 200, 50]: 1619
+New extrema at [1000000, 0.55, 250, 50]: 1136
+New extrema at [1000000, 0.55, 300, 50]: 681
+New extrema at [1000000, 0.55, 350, 50]: 462
+New extrema at [1000000, 0.55, 400, 50]: 292
+New extrema at [1000000, 0.55, 450, 50]: 232
+New extrema at [1000000, 0.55, 500, 50]: 105
[1000000, 0.55, 500, 50]
-False positive counts at [trials, success_rate, scale_circs, path_bias_pct]:
+False positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs scale_circs)
-New extrema at [1000000, 0.6, 100, 50]: 519
-New extrema at [1000000, 0.6, 150, 50]: 103
-New extrema at [1000000, 0.6, 200, 50]: 17
-New extrema at [1000000, 0.6, 250, 50]: 5
-New extrema at [1000000, 0.6, 300, 50]: 2
-New extrema at [1000000, 0.6, 350, 50]: 1
-New extrema at [1000000, 0.6, 450, 50]: 0
+New extrema at [1000000, 0.6, 100, 50]: 545
+New extrema at [1000000, 0.6, 150, 50]: 108
+New extrema at [1000000, 0.6, 200, 50]: 25
+New extrema at [1000000, 0.6, 250, 50]: 7
+New extrema at [1000000, 0.6, 300, 50]: 0
[1000000, 0.6, 500, 50]
-False positive counts at [trials, success_rate, scale_circs, path_bias_pct]:
+False positive counts at [num_circs, success_rate, scale_circs, path_bias_pct]:
(Results are some function of success_rate - path_bias_pct vs scale_circs)
-New extrema at [1000000, 0.45, 100, 30]: 17
+New extrema at [1000000, 0.45, 100, 30]: 16
New extrema at [1000000, 0.45, 150, 30]: 0
[1000000, 0.45, 500, 30]
@@ -171,17 +172,17 @@ New extrema at [1000000, 0.45, 150, 30]: 0
DoS attack durations (in circs) at [success_rate, dos_success_rate, path_bias_pct, scale_thresh]:
New extrema at [0.8, 0.05, 30, 200]: 150
New extrema at [0.8, 0.05, 30, 300]: 215
-New extrema at [0.8, 0.05, 30, 400]: 330
-New extrema at [0.8, 0.05, 30, 500]: 368
-New extrema at [0.8, 0.05, 30, 600]: 460
-New extrema at [0.8, 0.05, 30, 700]: 539
-New extrema at [0.8, 0.05, 30, 800]: 593
-New extrema at [0.8, 0.05, 30, 900]: 660
-New extrema at [0.8, 0.05, 30, 1000]: 760
+New extrema at [0.8, 0.05, 30, 400]: 310
+New extrema at [0.8, 0.05, 30, 500]: 380
+New extrema at [0.8, 0.05, 30, 600]: 465
+New extrema at [0.8, 0.05, 30, 700]: 510
+New extrema at [0.8, 0.05, 30, 800]: 658
+New extrema at [0.8, 0.05, 30, 900]: 675
+New extrema at [0.8, 0.05, 30, 1000]: 755
[0.8, 0.05, 30, 1000]
DoS attack durations (in circs) at [success_rate, dos_success_rate, path_bias_pct, scale_thresh]:
-New extrema at [0.8, 0.25, 30, 500]: 828
+New extrema at [0.8, 0.25, 30, 500]: 805
New extrema at [0.8, 0.15, 30, 500]: 503
-New extrema at [0.8, 0.04999999999999999, 30, 500]: 355
+New extrema at [0.8, 0.04999999999999999, 30, 500]: 362
[0.8, 0.04999999999999999, 30, 500]
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