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@@ -783,7 +783,8 @@ class Statistics:
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graphy.append(row[1])
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plt.autoscale(enable=True, axis='both')
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plt.title("Packet Rate")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Number of Packets')
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width = 0.5
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plt.xlim([0, len(graphx)])
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@@ -791,9 +792,9 @@ class Statistics:
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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@@ -811,27 +812,30 @@ class Statistics:
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for row in result:
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graphx.append(row[0])
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graphy.append(row[1])
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- plt.autoscale(enable=True, axis='both')
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- plt.title("Source IP Entropy")
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- plt.xlabel('Timestamp')
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- plt.ylabel('Entropy')
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- width = 0.5
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- plt.xlim([0, len(graphx)])
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- plt.grid(True)
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+ # If entropy was not calculated do not plot the graph
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+ if graphy[0] != -1:
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+ plt.autoscale(enable=True, axis='both')
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+ plt.title("Source IP Entropy")
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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+ plt.ylabel('Entropy')
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+ width = 0.5
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+ plt.xlim([0, len(graphx)])
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+ plt.grid(True)
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- # timestamp on x-axis
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- x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # timestamp on x-axis
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+ x = range(0, len(graphx))
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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- # limit the number of xticks
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- plt.locator_params(axis='x', nbins=20)
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+ # limit the number of xticks
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+ plt.locator_params(axis='x', nbins=20)
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- plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
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- out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-src-ent' + file_ending)
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- plt.savefig(out, dpi=500)
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- return out
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+ plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
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+ out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-src-ent' + file_ending)
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+ plt.savefig(out, dpi=500)
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+ return out
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def plot_interval_ip_dst_ent(file_ending: str):
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plt.gcf().clear()
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@@ -841,27 +845,30 @@ class Statistics:
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for row in result:
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graphx.append(row[0])
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graphy.append(row[1])
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- plt.autoscale(enable=True, axis='both')
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- plt.title("Destination IP Entropy")
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- plt.xlabel('Timestamp')
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- plt.ylabel('Entropy')
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- width = 0.5
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- plt.xlim([0, len(graphx)])
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- plt.grid(True)
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+ # If entropy was not calculated do not plot the graph
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+ if graphy[0] != -1:
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+ plt.autoscale(enable=True, axis='both')
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+ plt.title("Destination IP Entropy")
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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+ plt.ylabel('Entropy')
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+ width = 0.5
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+ plt.xlim([0, len(graphx)])
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+ plt.grid(True)
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- # timestamp on x-axis
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- x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # timestamp on x-axis
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+ x = range(0, len(graphx))
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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- # limit the number of xticks
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- plt.locator_params(axis='x', nbins=20)
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+ # limit the number of xticks
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+ plt.locator_params(axis='x', nbins=20)
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- plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
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- out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-dst-ent' + file_ending)
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- plt.savefig(out, dpi=500)
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- return out
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+ plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
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+ out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-dst-ent' + file_ending)
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+ plt.savefig(out, dpi=500)
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+ return out
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def plot_interval_ip_dst_cum_ent(file_ending: str):
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plt.gcf().clear()
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@@ -871,26 +878,29 @@ class Statistics:
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for row in result:
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graphx.append(row[0])
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graphy.append(row[1])
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- plt.autoscale(enable=True, axis='both')
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- plt.title("Destination IP Cumulative Entropy")
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- plt.xlabel('Timestamp')
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- plt.ylabel('Entropy')
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- plt.xlim([0, len(graphx)])
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- plt.grid(True)
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+ # If entropy was not calculated do not plot the graph
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+ if graphy[0] != -1:
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+ plt.autoscale(enable=True, axis='both')
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+ plt.title("Destination IP Cumulative Entropy")
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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+ plt.ylabel('Entropy')
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+ plt.xlim([0, len(graphx)])
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+ plt.grid(True)
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- # timestamp on x-axis
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- x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # timestamp on x-axis
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+ x = range(0, len(graphx))
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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- # limit the number of xticks
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- plt.locator_params(axis='x', nbins=20)
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+ # limit the number of xticks
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+ plt.locator_params(axis='x', nbins=20)
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- plt.plot(x, graphy, 'r')
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- out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-dst-cum-ent' + file_ending)
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- plt.savefig(out, dpi=500)
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- return out
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+ plt.plot(x, graphy, 'r')
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+ out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-dst-cum-ent' + file_ending)
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+ plt.savefig(out, dpi=500)
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+ return out
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def plot_interval_ip_src_cum_ent(file_ending: str):
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plt.gcf().clear()
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@@ -901,27 +911,29 @@ class Statistics:
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for row in result:
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graphx.append(row[0])
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graphy.append(row[1])
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+ # If entropy was not calculated do not plot the graph
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+ if graphy[0] != -1:
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+ plt.autoscale(enable=True, axis='both')
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+ plt.title("Source IP Cumulative Entropy")
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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+ plt.ylabel('Entropy')
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+ plt.xlim([0, len(graphx)])
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+ plt.grid(True)
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- plt.autoscale(enable=True, axis='both')
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- plt.title("Source IP Cumulative Entropy")
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- plt.xlabel('Timestamp')
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- plt.ylabel('Entropy')
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- plt.xlim([0, len(graphx)])
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- plt.grid(True)
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-
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- # timestamp on x-axis
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- x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # timestamp on x-axis
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+ x = range(0, len(graphx))
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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- # limit the number of xticks
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- plt.locator_params(axis='x',nbins=20)
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+ # limit the number of xticks
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+ plt.locator_params(axis='x',nbins=20)
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- plt.plot(x, graphy, 'r')
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- out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-src-cum-ent' + file_ending)
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- plt.savefig(out, dpi=500)
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- return out
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+ plt.plot(x, graphy, 'r')
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+ out = self.pcap_filepath.replace('.pcap', '_plot-interval-ip-src-cum-ent' + file_ending)
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+ plt.savefig(out, dpi=500)
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+ return out
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def plot_interval_new_ip(file_ending: str):
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plt.gcf().clear()
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@@ -934,7 +946,8 @@ class Statistics:
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plt.autoscale(enable=True, axis='both')
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plt.title("IP Novelty Distribution")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Novel values count')
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plt.xlim([0, len(graphx)])
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plt.grid(True)
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@@ -942,9 +955,9 @@ class Statistics:
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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@@ -965,7 +978,8 @@ class Statistics:
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plt.autoscale(enable=True, axis='both')
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plt.title("Port Novelty Distribution")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Novel values count')
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plt.xlim([0, len(graphx)])
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plt.grid(True)
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@@ -973,9 +987,9 @@ class Statistics:
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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@@ -997,7 +1011,8 @@ class Statistics:
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plt.autoscale(enable=True, axis='both')
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plt.title("TTL Novelty Distribution")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Novel values count')
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plt.xlim([0, len(graphx)])
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plt.grid(True)
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@@ -1005,9 +1020,9 @@ class Statistics:
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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@@ -1030,16 +1045,17 @@ class Statistics:
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plt.autoscale(enable=True, axis='both')
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plt.title("ToS Novelty Distribution")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Novel values count')
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plt.xlim([0, len(graphx)])
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plt.grid(True)
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width = 0.5
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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@@ -1061,7 +1077,8 @@ class Statistics:
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plt.autoscale(enable=True, axis='both')
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plt.title("Window Size Novelty Distribution")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Novel values count')
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plt.xlim([0, len(graphx)])
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plt.grid(True)
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@@ -1069,9 +1086,9 @@ class Statistics:
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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@@ -1096,7 +1113,8 @@ class Statistics:
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plt.autoscale(enable=True, axis='both')
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plt.title("MSS Novelty Distribution")
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- plt.xlabel('Timestamp')
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+ # plt.xlabel('Timestamp')
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+ plt.xlabel('Time Interval')
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plt.ylabel('Novel values count')
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plt.xlim([0, len(graphx)])
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plt.grid(True)
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@@ -1104,9 +1122,9 @@ class Statistics:
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# timestamp on x-axis
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x = range(0, len(graphx))
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- my_xticks = graphx
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- plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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- plt.tight_layout()
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+ # my_xticks = graphx
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+ # plt.xticks(x, my_xticks, rotation='vertical', fontsize=5)
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+ # plt.tight_layout()
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# limit the number of xticks
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plt.locator_params(axis='x', nbins=20)
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aidmar.wainakh