Chapter 12. Volume and Time Analysis

In this chapter, we look at phenomena that can be identified by comparing traffic volume against the passage of time. “Volume” may be a simple count of the number of bytes or packets, or it may be a construct such as the number of IP addresses transferring files. Based on the traffic observed, there are a number of different phenomena that can be pulled out of traffic data, particularly:

Beaconing
When someone contacts your host at regular intervals, it is a possible sign of an attack.
File extraction
Massive downloads are suggestive of someone stealing your internal data.
Denial of Service (DoS)
Preventing your servers from providing service.

Traffic volume data is noisy. Most of the observables that you can directly count, such as the number of bytes over time, vary highly and have no real relationship between the volume of the event and its significance. In other words, there’s rarely a significant relationship between the number of bytes and the importance of the events. This chapter will help you find unusual behaviors through scripts and visualizations, but a certain amount of human eyeballing and judgment are necessary to determine which behaviors to consider dangerous.

The Workday and Its Impact on Network Traffic Volume

The bulk of traffic on an enterprise network comes from people who are paid to work there, so their traffic is going to roughly follow the hours of the business day. Traffic will trough during the evening, rise around ...

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