Add better support to obfuscate statistics.

src/common/util.c

@@ -513,6 +513,51 @@ round_uint64_to_next_multiple_of(uint64_t number, uint64_t divisor)
   return number;
 }
 
+/** Return the lowest x in [INT64_MIN, INT64_MAX] such that x is at least
+ * <b>number</b>, and x modulo <b>divisor</b> == 0. */
+int64_t
+round_int64_to_next_multiple_of(int64_t number, int64_t divisor)
+{
+  tor_assert(divisor > 0);
+  if (number >= 0 && INT64_MAX - divisor + 1 >= number)
+    number += divisor - 1;
+  number -= number % divisor;
+  return number;
+}
+
+/** Transform a random value <b>p</b> from the uniform distribution in
+ * [0.0, 1.0[ into a Laplace distributed value with location parameter
+ * <b>mu</b> and scale parameter <b>b</b> in [-Inf, Inf[. */
+double
+sample_laplace_distribution(double mu, double b, double p)
+{
+  tor_assert(p >= 0.0 && p < 1.0);
+  /* This is the "inverse cumulative distribution function" from:
+   * http://en.wikipedia.org/wiki/Laplace_distribution */
+  return mu - b * (p > 0.5 ? 1.0 : -1.0)
+                * tor_mathlog(1.0 - 2.0 * fabs(p - 0.5));
+}
+
+/** Add random noise between INT64_MIN and INT64_MAX coming from a
+ * Laplace distribution with mu = 0 and b = <b>delta_f</b>/<b>epsilon</b>
+ * to <b>signal</b> based on the provided <b>random</b> value in
+ * [0.0, 1.0[. */
+int64_t
+add_laplace_noise(int64_t signal, double random, double delta_f,
+                  double epsilon)
+{
+  /* cast to int64_t intended */
+  int64_t noise = sample_laplace_distribution(
+               0.0, /* just add noise, no further signal */
+               delta_f / epsilon, random);
+  if (noise > 0 && INT64_MAX - noise < signal)
+    return INT64_MAX;
+  else if (noise < 0 && INT64_MIN - noise > signal)
+    return INT64_MIN;
+  else
+    return signal + noise;
+}
+
 /** Return the number of bits set in <b>v</b>. */
 int
 n_bits_set_u8(uint8_t v)

src/common/util.h

@@ -172,6 +172,10 @@ uint64_t round_to_power_of_2(uint64_t u64);
 unsigned round_to_next_multiple_of(unsigned number, unsigned divisor);
 uint32_t round_uint32_to_next_multiple_of(uint32_t number, uint32_t divisor);
 uint64_t round_uint64_to_next_multiple_of(uint64_t number, uint64_t divisor);
+int64_t round_int64_to_next_multiple_of(int64_t number, int64_t divisor);
+double sample_laplace_distribution(double mu, double b, double p);
+int64_t add_laplace_noise(int64_t signal, double random, double delta_f,
+                          double epsilon);
 int n_bits_set_u8(uint8_t v);
 
 /* Compute the CEIL of <b>a</b> divided by <b>b</b>, for nonnegative <b>a</b>

src/test/test_util.c

@@ -4619,6 +4619,58 @@ test_util_round_to_next_multiple_of(void *arg)
   tt_assert(round_uint64_to_next_multiple_of(99,7) == 105);
   tt_assert(round_uint64_to_next_multiple_of(99,9) == 99);
 
+  tt_assert(round_int64_to_next_multiple_of(0,1) == 0);
+  tt_assert(round_int64_to_next_multiple_of(0,7) == 0);
+
+  tt_assert(round_int64_to_next_multiple_of(99,1) == 99);
+  tt_assert(round_int64_to_next_multiple_of(99,7) == 105);
+  tt_assert(round_int64_to_next_multiple_of(99,9) == 99);
+
+  tt_assert(round_int64_to_next_multiple_of(-99,1) == -99);
+  tt_assert(round_int64_to_next_multiple_of(-99,7) == -98);
+  tt_assert(round_int64_to_next_multiple_of(-99,9) == -99);
+
+  tt_assert(round_int64_to_next_multiple_of(INT64_MIN,2) == INT64_MIN);
+  tt_assert(round_int64_to_next_multiple_of(INT64_MAX,2) ==
+                                            INT64_MAX-INT64_MAX%2);
+ done:
+  ;
+}
+
+static void
+test_util_laplace(void *arg)
+{
+  /* Sample values produced using Python's SciPy:
+   *
+   * >>> from scipy.stats import laplace
+   * >>> laplace.ppf([-0.01, 0.0, 0.01, 0.5, 0.51, 0.99, 1.0, 1.01],
+     ...             loc = 24, scale = 24)
+   * array([          nan,          -inf,  -69.88855213,   24.        ,
+   *          24.48486498,  117.88855213,           inf,           nan])
+   */
+  const double mu = 24.0, b = 24.0;
+  const double delta_f = 15.0, epsilon = 0.3; /* b = 15.0 / 0.3 = 50.0 */
+  (void)arg;
+
+  tt_assert(isinf(sample_laplace_distribution(mu, b, 0.0)));
+  test_feq(-69.88855213, sample_laplace_distribution(mu, b, 0.01));
+  test_feq(24.0, sample_laplace_distribution(mu, b, 0.5));
+  test_feq(24.48486498, sample_laplace_distribution(mu, b, 0.51));
+  test_feq(117.88855213, sample_laplace_distribution(mu, b, 0.99));
+
+  /* >>> laplace.ppf([0.0, 0.1, 0.25, 0.5, 0.75, 0.9, 0.99],
+   * ...             loc = 0, scale = 50)
+   * array([         -inf,  -80.47189562,  -34.65735903,    0.        ,
+   *          34.65735903,   80.47189562,  195.60115027])
+   */
+  tt_assert(LONG_MIN + 20 ==
+            add_laplace_noise(20, 0.0, delta_f, epsilon));
+  tt_assert(-60 == add_laplace_noise(20, 0.1, delta_f, epsilon));
+  tt_assert(-14 == add_laplace_noise(20, 0.25, delta_f, epsilon));
+  tt_assert(20 == add_laplace_noise(20, 0.5, delta_f, epsilon));
+  tt_assert(54 == add_laplace_noise(20, 0.75, delta_f, epsilon));
+  tt_assert(100 == add_laplace_noise(20, 0.9, delta_f, epsilon));
+  tt_assert(215 == add_laplace_noise(20, 0.99, delta_f, epsilon));
  done:
   ;
 }
@@ -4880,6 +4932,7 @@ struct testcase_t util_tests[] = {
   UTIL_LEGACY(strtok),
   UTIL_LEGACY(di_ops),
   UTIL_TEST(round_to_next_multiple_of, 0),
+  UTIL_TEST(laplace, 0),
   UTIL_TEST(strclear, 0),
   UTIL_TEST(find_str_at_start_of_line, 0),
   UTIL_TEST(string_is_C_identifier, 0),