chrome/renderer/safe_browsing/scorer_unittest.cc

   1 // Copyright (c) 2011 The Chromium Authors. All rights reserved.
   2 // Use of this source code is governed by a BSD-style license that can be
   3 // found in the LICENSE file.
   4
   5 #include "chrome/renderer/safe_browsing/scorer.h"
   6
   7 #include "base/containers/hash_tables.h"
   8 #include "base/files/file_path.h"
   9 #include "base/files/scoped_temp_dir.h"
  10 #include "base/format_macros.h"
  11 #include "base/memory/scoped_ptr.h"
  12 #include "base/message_loop/message_loop.h"
  13 #include "base/threading/thread.h"
  14 #include "chrome/common/safe_browsing/client_model.pb.h"
  15 #include "chrome/renderer/safe_browsing/features.h"
  16 #include "testing/gmock/include/gmock/gmock.h"
  17 #include "testing/gtest/include/gtest/gtest.h"
  18
  19 namespace safe_browsing {
  20
  21 class PhishingScorerTest : public ::testing::Test {
  22  protected:
  23   virtual void SetUp() {
  24     // Setup a simple model.  Note that the scorer does not care about
  25     // how features are encoded so we use readable strings here to make
  26     // the test simpler to follow.
  27     model_.Clear();
  28     model_.add_hashes("feature1");
  29     model_.add_hashes("feature2");
  30     model_.add_hashes("feature3");
  31     model_.add_hashes("token one");
  32     model_.add_hashes("token two");
  33
  34     ClientSideModel::Rule* rule;
  35     rule = model_.add_rule();
  36     rule->set_weight(0.5);
  37
  38     rule = model_.add_rule();
  39     rule->add_feature(0);  // feature1
  40     rule->set_weight(2.0);
  41
  42     rule = model_.add_rule();
  43     rule->add_feature(0);  // feature1
  44     rule->add_feature(1);  // feature2
  45     rule->set_weight(3.0);
  46
  47     model_.add_page_term(3);  // token one
  48     model_.add_page_term(4);  // token two
  49
  50     // These will be murmur3 hashes, but for this test it's not necessary
  51     // that the hashes correspond to actual words.
  52     model_.add_page_word(1000U);
  53     model_.add_page_word(2000U);
  54     model_.add_page_word(3000U);
  55
  56     model_.set_max_words_per_term(2);
  57     model_.set_murmur_hash_seed(12345U);
  58   }
  59
  60   ClientSideModel model_;
  61 };
  62
  63 TEST_F(PhishingScorerTest, HasValidModel) {
  64   scoped_ptr<Scorer> scorer;
  65   scorer.reset(Scorer::Create(model_.SerializeAsString()));
  66   EXPECT_TRUE(scorer.get() != NULL);
  67
  68   // Invalid model string.
  69   scorer.reset(Scorer::Create("bogus string"));
  70   EXPECT_FALSE(scorer.get());
  71
  72   // Mode is missing a required field.
  73   model_.clear_max_words_per_term();
  74   scorer.reset(Scorer::Create(model_.SerializePartialAsString()));
  75   EXPECT_FALSE(scorer.get());
  76 }
  77
  78 TEST_F(PhishingScorerTest, PageTerms) {
  79   scoped_ptr<Scorer> scorer(Scorer::Create(model_.SerializeAsString()));
  80   ASSERT_TRUE(scorer.get());
  81   base::hash_set<std::string> expected_page_terms;
  82   expected_page_terms.insert("token one");
  83   expected_page_terms.insert("token two");
  84   EXPECT_THAT(scorer->page_terms(),
  85               ::testing::ContainerEq(expected_page_terms));
  86 }
  87
  88 TEST_F(PhishingScorerTest, PageWords) {
  89   scoped_ptr<Scorer> scorer(Scorer::Create(model_.SerializeAsString()));
  90   ASSERT_TRUE(scorer.get());
  91   base::hash_set<uint32> expected_page_words;
  92   expected_page_words.insert(1000U);
  93   expected_page_words.insert(2000U);
  94   expected_page_words.insert(3000U);
  95   EXPECT_THAT(scorer->page_words(),
  96               ::testing::ContainerEq(expected_page_words));
  97   EXPECT_EQ(2U, scorer->max_words_per_term());
  98   EXPECT_EQ(12345U, scorer->murmurhash3_seed());
  99 }
 100
 101 TEST_F(PhishingScorerTest, ComputeScore) {
 102   scoped_ptr<Scorer> scorer(Scorer::Create(model_.SerializeAsString()));
 103   ASSERT_TRUE(scorer.get());
 104
 105   // An empty feature map should match the empty rule.
 106   FeatureMap features;
 107   // The expected logodds is 0.5 (empty rule) => p = exp(0.5) / (exp(0.5) + 1)
 108   // => 0.62245933120185459
 109   EXPECT_DOUBLE_EQ(0.62245933120185459, scorer->ComputeScore(features));
 110   // Same if the feature does not match any rule.
 111   EXPECT_TRUE(features.AddBooleanFeature("not existing feature"));
 112   EXPECT_DOUBLE_EQ(0.62245933120185459, scorer->ComputeScore(features));
 113
 114   // Feature 1 matches which means that the logodds will be:
 115   //   0.5 (empty rule) + 2.0 (rule weight) * 0.15 (feature weight) = 0.8
 116   //   => p = 0.6899744811276125
 117   EXPECT_TRUE(features.AddRealFeature("feature1", 0.15));
 118   EXPECT_DOUBLE_EQ(0.6899744811276125, scorer->ComputeScore(features));
 119
 120   // Now, both feature 1 and feature 2 match.  Expected logodds:
 121   //   0.5 (empty rule) + 2.0 (rule weight) * 0.15 (feature weight) +
 122   //   3.0 (rule weight) * 0.15 (feature1 weight) * 1.0 (feature2) weight = 9.8
 123   //   => p = 0.99999627336071584
 124   EXPECT_TRUE(features.AddBooleanFeature("feature2"));
 125   EXPECT_DOUBLE_EQ(0.77729986117469119, scorer->ComputeScore(features));
 126 }
 127 }  // namespace safe_browsing