#id_incidents = [24,25,26,19,27] #id_incidents = [29,30,31,32,33,34] id_incidents = [29,30,42,31,32,33,34] #bothound_tools.calculate_attack_metrics(id_incidents) #id_incident, id_attack, cluster_indexes1, cluster_indexes2, id_incidents, features = [] #bothound_tools.calculate_distances(id_incident = 29, id_attack = 1, cluster_indexes1 = [], cluster_indexes2 = [], # id_incidents = [29,30,31,32,33,34,36,37,39,40,42], features = []) #bothound_tools.calculate_common_ips([29,30,31,32,33,34], 1, [36,37,39,40]) bothound_tools.incidents_summary(id_incidents) attacks = bothound_tools.get_attacks(id_incidents) # show attack count for a in attacks: print a #bothound_tools.get_top_attack_countries(id_incidents) #bothound_tools.extract_attack_ips(id_incidents) #analytics.calculate_intersection_with_file(id_incidents, # "./botnet_xmlrpc_20160414.csv", "intersection_botnet_xmlrpc_20160414.txt") #for i in range(1, 9): # bothound_tools.extract_attack_ips(id_incidents, i) #analytics.calculate_cross_table(id_incidents)
