commit 4a30e7a9fbdded5318506302543b5d5e07571670 Author: Karsten Loesing karsten.loesing@gmx.net Date: Mon Mar 12 17:49:40 2018 +0100

Remove unused code from the censorship detector. --- src/main/python/clients/detector.py | 199 +----------------------------------- 1 file changed, 2 insertions(+), 197 deletions(-)

diff --git a/src/main/python/clients/detector.py b/src/main/python/clients/detector.py index 6cf1c7d..3d17bf0 100644 --- a/src/main/python/clients/detector.py +++ b/src/main/python/clients/detector.py @@ -60,8 +60,6 @@ import country_info # write utf8 to file import codecs

-days = ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"] - def get_country_name_from_cc(country_code): if (country_code.lower() in country_info.countries): return country_info.countries[country_code.lower()] @@ -208,145 +206,6 @@ def make_tendencies_minmax(l, INTERVAL = 1): ## print minx[-1], maxx[-1] return minx, maxx

-# Makes pretty plots -def raw_plot(series, minc, maxc, labels, xtitle): - assert len(xtitle) == 3 - fname, stitle, slegend = xtitle - - font = {'family' : 'Bitstream Vera Sans', - 'weight' : 'normal', - 'size' : 8} - matplotlib.rc('font', **font) - - ylim( (-max(series)*0.1, max(series)*1.1) ) - plot(labels, series, linewidth=1.0, label="Users") - - wherefill = [] - for mm,mx in zip(minc, maxc): - wherefill += [not (mm == None and mx == None)] - assert mm < mx or (mm == None and mx == None) - - fill_between(labels, minc, maxc, where=wherefill, color="gray", label="Prediction") - - vdown = [] - vup = [] - for i,v in enumerate(series): - if minc[i] != None and v < minc[i]: - vdown += [v] - vup += [None] - elif maxc[i] != None and v > maxc[i]: - vdown += [None] - vup += [v] - else: - vup += [None] - vdown += [None] - - plot(labels, vdown, 'o', ms=10, lw=2, alpha=0.5, mfc='orange', label="Downturns") - plot(labels, vup, 'o', ms=10, lw=2, alpha=0.5, mfc='green', label="Upturns") - - legend(loc=2) - - xlabel('Time (days)') - ylabel('Users') - title(stitle) - grid(True) - F = gcf() - - F.set_size_inches(10,5) - F.savefig(fname, format="png", dpi = (150)) - close() - -def absolute_plot(series, minc, maxc, labels,INTERVAL, xtitle): - in_minc = [] - in_maxc = [] - for i, v in enumerate(series): - if i > 0 and i - INTERVAL >= 0 and series[i] != None and series[i-INTERVAL] != None and series[i-INTERVAL] != 0 and minc[i]!= None and maxc[i]!= None: - in_minc += [minc[i] * poisson.ppf(1-0.9999, series[i-INTERVAL])] - in_maxc += [maxc[i] * poisson.ppf(0.9999, series[i-INTERVAL])] - if not in_minc[-1] < in_maxc[-1]: - print in_minc[-1], in_maxc[-1], series[i-INTERVAL], minc[i], maxc[i] - assert in_minc[-1] < in_maxc[-1] - else: - in_minc += [None] - in_maxc += [None] - raw_plot(series, in_minc, in_maxc, labels, xtitle) - -"""Return the number of downscores and upscores of a time series -'series', given tendencies 'minc' and 'maxc' for the time interval -'INTERVAL'. - -If 'scoring_interval' is specifed we only consider upscore/downscore -that happened in the latest 'scoring_interval' days. -""" -def censor_score(series, minc, maxc, INTERVAL, scoring_interval=None): - upscore = 0 - downscore = 0 - - if scoring_interval is None: - scoring_interval = len(series) - assert(len(series) >= scoring_interval) - - for i, v in enumerate(series): - if i > 0 and i - INTERVAL >= 0 and series[i] != None and series[i-INTERVAL] != None and series[i-INTERVAL] != 0 and minc[i]!= None and maxc[i]!= None: - in_minc = minc[i] * poisson.ppf(1-0.9999, series[i-INTERVAL]) - in_maxc = maxc[i] * poisson.ppf(0.9999, series[i-INTERVAL]) - if (i >= (len(series) - scoring_interval)): - downscore += 1 if minc[i] != None and v < in_minc else 0 - upscore += 1 if maxc[i] != None and v > in_maxc else 0 - - return downscore, upscore - -def plot_target(tss, TARGET, xtitle, minx, maxx, DAYS=365, INTERV = 7): - ctarget = tss.get_country_series(TARGET) - c = n_day_rel(ctarget, INTERV) - absolute_plot(ctarget[-DAYS:], minx[-DAYS:], maxx[-DAYS:], tss.all_dates[-DAYS:],INTERV, xtitle = xtitle) - -def write_censorship_report_prologue(report_file, dates, notification_period): - if (notification_period == 1): - date_str = "%s" % (dates[-1]) # no need for date range if it's just one day - else: - date_str = "%s to %s" % (dates[-notification_period], dates[-1]) - - prologue = "=======================\n" - prologue += "Automatic Censorship Report for %s\n" % (date_str) - prologue += "=======================\n\n" - report_file.write(prologue) - -## Make a league table of censorship + nice graphs -def plot_all(tss, minx, maxx, INTERV, DAYS=None, rdir="img"): - rdir = os.path.realpath(rdir) - if not os.path.exists(rdir) or not os.path.isdir(rdir): - print "ERROR: %s does not exist or is not a directory." % rdir - return - - summary_file = file(os.path.join(rdir, "summary.txt"), "w") - - if DAYS == None: - DAYS = 6*31 - - s = tss.get_largest(200) - scores = [] - for num, li in s: - print ".", - ds,us = censor_score(tss.get_country_series(li)[-DAYS:], minx[-DAYS:], maxx[-DAYS:], INTERV) - # print ds, us - scores += [(ds,num, us, li)] - scores.sort() - scores.reverse() - s = "\n=======================\n" - s+= "Report for %s to %s\n" % (tss.all_dates[-DAYS], tss.all_dates[-1]) - s+= "=======================\n" - print s - summary_file.write(s) - for a,nx, b,c in scores: - if a > 0: - s = "%s -- down: %2d (up: %2d affected: %s)" % (c, a, b, nx) - print s - summary_file.write(s + "\n") - xtitle = (os.path.join(rdir, "%03d-%s-censor.png" % (a,c)), "Tor report for %s -- down: %2d (up: %2d affected: %s)" % (c, a, b, nx),"") - plot_target(tss, c,xtitle, minx, maxx, DAYS, INTERV) - summary_file.close() - """Write a CSV report on the minimum/maximum users of each country per date.""" def write_all(tss, minc, maxc, RANGES_FILE, INTERVAL=7): ranges_file = file(RANGES_FILE, "w") @@ -368,70 +227,16 @@ def write_all(tss, minc, maxc, RANGES_FILE, INTERVAL=7): ranges_file.write("%s,%s,%s,%s\n" % (tss.all_dates[i], c, minv, maxv)) ranges_file.close()

-"""Return a URL that points to a graph in metrics.tpo that displays -the number of direct Tor users in country 'country_code', for a -'period'-days period. - -Let's hope that the metrics.tpo URL scheme doesn't change often. -""" -def get_tor_usage_graph_url_for_cc_and_date(country_code, dates, period): - url = "https://metrics.torproject.org/users.html?graph=userstats-relay-country&..." % \ - (dates[-period], dates[-1], country_code) - return url - -"""Write a file containing a short censorship report over the last -'notification_period' days. -""" -def write_ml_report(tss, minx, maxx, INTERV, DAYS, notification_period=None): - if notification_period is None: - notification_period = DAYS - - report_file = codecs.open('short_censorship_report.txt', 'w', 'utf-8') - file_prologue_written = False - - s = tss.get_largest(None) # no restrictions, get 'em all. - scores = [] - for num, li in s: - ds,us = censor_score(tss.get_country_series(li)[-DAYS:], minx[-DAYS:], maxx[-DAYS:], INTERV, notification_period) - scores += [(ds,num, us, li)] - scores.sort() - scores.reverse() - - for downscores,users_n,upscores,country_code in scores: - if (downscores > 0) or (upscores > 0): - if not file_prologue_written: - write_censorship_report_prologue(report_file, tss.all_dates, notification_period) - file_prologue_written = True - - if ((upscores > 0) and (downscores == 0)): - s = "We detected an unusual spike of Tor users in %s (%d upscores, %d users):\n" % \ - (get_country_name_from_cc(country_code), upscores, users_n) - else: - s = "We detected %d potential censorship events in %s (users: %d, upscores: %d):\n" % \ - (downscores, get_country_name_from_cc(country_code), users_n, upscores) - - # Also give out a link for the appropriate usage graph for a 90-days period. - s += get_tor_usage_graph_url_for_cc_and_date(country_code, tss.all_dates, 90) - - report_file.write(s + "\n") - - report_file.close() - # INTERV is the time interval to model connection rates; # consider maximum DAYS days back. def detect(CSV_FILE = "userstats-detector.csv", - RANGES_FILE = "userstats-ranges.csv", GRAPH_DIR = "img", - INTERV = 7, DAYS = 6 * 31, REPORT = True): + RANGES_FILE = "userstats-ranges.csv", + INTERV = 7, DAYS = 6 * 31): tss = torstatstore(CSV_FILE) l = tss.get_largest_locations(50) minx, maxx = make_tendencies_minmax(l, INTERV) - #plot_all(tss, minx, maxx, INTERV, DAYS, rdir=GRAPH_DIR) write_all(tss, minx, maxx, RANGES_FILE, INTERV)

- if REPORT: - # Make our short report; only consider events of the last day - write_ml_report(tss, minx, maxx, INTERV, DAYS, 1) - def main(): detect()