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Calculate novelty based on distance from observed prints.

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david
2012-01-17 20:33:19 +00:00
parent eb82de88db
commit 6ca2b871b6
1 changed files with 33 additions and 3 deletions
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36
FPEngine.cc
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@@ -665,6 +665,8 @@ FPEngine6::~FPEngine6() {
/* From FPModel.cc. */
extern struct model FPModel;
extern double FPscale[][2];
extern double FPmean[][659];
extern double FPvariance[][659];
extern FingerMatch FPmatches[];
/* Not all operating systems allow setting the flow label in outgoing packets;
@@ -926,7 +928,33 @@ int label_prob_cmp(const void *a, const void *b) {
#define NOVELTY_THRESHOLD 10.0
static double novelty_of(const struct feature_node *features, int label) {
return 0.0;
const double *means, *variances;
int i, nr_feature;
double sum;
nr_feature = get_nr_feature(&FPModel);
assert(0 <= label);
assert(label < nr_feature);
means = FPmean[label];
variances = FPvariance[label];
sum = 0.0;
for (i = 0; i < nr_feature; i++) {
double d, v;
assert(i + 1 == features[i].index);
d = features[i].value - means[i];
v = variances[i];
if (v == 0.0) {
/* No variance? It means that samples were identical. Substitute a sample
variance. */
v = 1.0;
}
sum += d * d / v;
}
return sqrt(sum);
}
static void classify(FingerPrintResultsIPv6 *FPR) {
@@ -955,8 +983,10 @@ static void classify(FingerPrintResultsIPv6 *FPR) {
FPR->num_matches = i + 1;
if (labels[i].prob >= 0.90 * labels[0].prob)
FPR->num_perfect_matches = i + 1;
if (o.debugging > 2)
printf("%7.4f %3u %s\n", FPR->accuracy[i] * 100, labels[i].label, FPR->matches[i]->OS_name);
if (o.debugging > 2) {
printf("%7.4f %7.4f %3u %s\n", FPR->accuracy[i] * 100,
novelty_of(features, labels[i].label), labels[i].label, FPR->matches[i]->OS_name);
}
}
if (FPR->num_perfect_matches == 0) {
FPR->overall_results = OSSCAN_NOMATCHES;