Strategic Planning for Network Data Analysis
  As network traffic monitoring software for cybersecurity, malware detection,
and other critical tasks becomes increasingly automated, the rate of alerts and
supporting data gathered, as well as the complexity of the underlying model,
regularly exceed human processing capabilities. Many of these applications
require complex models and constituent rules in order to come up with decisions
that influence the operation of entire systems. In this paper, we motivate the
novel "strategic planning" problem -- one of gathering data from the world and
applying the underlying model of the domain in order to come up with decisions
that will monitor the system in an automated manner. We describe our use of
automated planning methods to this problem, including the technique that we
used to solve it in a manner that would scale to the demands of a real-time,
real world scenario. We then present a PDDL model of one such application
scenario related to network administration and monitoring, followed by a
description of a novel integrated system that was built to accept generated
plans and to continue the execution process. Finally, we present evaluations of
two different automated planners and their different capabilities with our
integrated system, both on a six-month window of network data, and using a
simulator.
