commit 7cd53b75c10831e01e288b01f63cab069d3e3035 Author: Karsten Loesing karsten.loesing@gmx.net Date: Mon Dec 8 15:00:58 2014 +0100
Add better support to obfuscate statistics. --- src/common/util.c | 45 ++++++++++++++++++++++++++++++++++++++++++ src/common/util.h | 4 ++++ src/test/test_util.c | 53 ++++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 102 insertions(+)
diff --git a/src/common/util.c b/src/common/util.c index 50097da..c52b279 100644 --- a/src/common/util.c +++ b/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) diff --git a/src/common/util.h b/src/common/util.h index 921dd79..b8fd20f 100644 --- a/src/common/util.h +++ b/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> diff --git a/src/test/test_util.c b/src/test/test_util.c index b952bb2..6e73ccf 100644 --- a/src/test/test_util.c +++ 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),