commit 04ed8e5dc3b357f6d7c012b6192f7c841b04aaed Author: Mike Perry <mikeperry-git@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]