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Avoiding duplicates in neural clusters

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BlackLight 2011-02-15 14:09:50 +01:00
parent b49e9152ec
commit 593a752ecf
1 changed files with 38 additions and 3 deletions
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41
neural_cluster.c
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@ -45,7 +45,7 @@
PRIVATE void
__AI_neural_clusters_to_xml ( kmeans_t *km, AI_alerts_per_neuron *alerts_per_neuron )
{
int i, j, k, l, are_equal;
int i, j, k, l, m, n, are_equal;
FILE *fp = NULL;
uint32_t src_addr = 0,
@ -57,8 +57,9 @@ __AI_neural_clusters_to_xml ( kmeans_t *km, AI_alerts_per_neuron *alerts_per_neu
*tmp = NULL,
*buf = NULL;
AI_alerts_per_neuron_key key;
AI_alerts_per_neuron *alert_iterator = NULL;
AI_alerts_per_neuron_key key, tmp_key;
AI_alerts_per_neuron *alert_iterator = NULL,
*tmp_iterator = NULL;
if ( !( fp = fopen ( config->neural_clusters_log, "w" )))
{
@ -106,6 +107,40 @@ __AI_neural_clusters_to_xml ( kmeans_t *km, AI_alerts_per_neuron *alerts_per_neu
}
}
/* If no duplicate alert was found on the same neuron, check
* that there is no duplicate alert on other neurons */
if ( !are_equal )
{
for ( l=0; l <= i && !are_equal; l++ )
{
for ( m=0; m < j && !are_equal; m++ )
{
tmp_key.x = km->clusters[l][m][0];
tmp_key.y = km->clusters[l][m][1];
HASH_FIND ( hh, alerts_per_neuron, &tmp_key, sizeof ( tmp_key ), tmp_iterator );
if ( tmp_iterator )
{
for ( n=0; n < tmp_iterator->n_alerts && !are_equal; n++ )
{
if (
alert_iterator->alerts[k].gid == tmp_iterator->alerts[n].gid &&
alert_iterator->alerts[k].sid == tmp_iterator->alerts[n].sid &&
alert_iterator->alerts[k].rev == tmp_iterator->alerts[n].rev &&
alert_iterator->alerts[k].src_ip_addr == tmp_iterator->alerts[n].src_ip_addr &&
alert_iterator->alerts[k].dst_ip_addr == tmp_iterator->alerts[n].dst_ip_addr &&
alert_iterator->alerts[k].src_port == tmp_iterator->alerts[n].src_port &&
alert_iterator->alerts[k].dst_port == tmp_iterator->alerts[n].dst_port &&
alert_iterator->alerts[k].timestamp == tmp_iterator->alerts[n].timestamp )
{
are_equal = 1;
}
}
}
}
}
}
if ( !are_equal )
{
src_addr = htonl ( alert_iterator->alerts[k].src_ip_addr );