Find public information about an event that had an impact on Internet connectivity for individual AS or entire countries. Example types of events are DDoS attacks, prefix hijacking, political developments, social unrest, social media censorship, an earthquake, or other physical phenomena.

Identify a metric that is associated with the control plane behavior of one impacted AS. Briefly justify why your metric is relevant. Use the PyBGPstream library to study/track this metric. Example metrics are the number of prefixes that are advertised by an origin AS, the duration between Announcement and Withdrawal for a prefix, the AS path and any changes it is associated with, change of origin AS for a prefix, advertisements with conflicting multiple origin AS for a single prefix, etc. The code should pull data, process it and produce the metric value. Hardcoded values are not acceptable, the result should be reproducible by running the code.

Show a line graph using matplot lib with the metric of your choice before, during and after the event took place. The goal of this graph is to show that an aspect of the control plane behavior of a network is clearly atypical during the event. So, the x-axis of the line graph will reflect time (in a timescale of your choice), and the y-axis will show your metric.

import pybgpstream

from matplotlib import pyplot as plt