Active Perception for Cyber Intrusion Detection and Defense

Abstract

This paper describes an automated process of active perception for cyber defense. Our approach is informed by theoretical ideas from decision theory and recent research results in neuroscience. Our cognitive agent allocates computational and sensing resources to (approximately) optimize its Value of Information. To do this, it draws on models to direct sensors towards phenomena of greatest interest to inform decisions about cyber defense actions. By identifying critical network assets, the organization's mission measures interest (and value of information). This model enables the system to follow leads from inexpensive, inaccurate alerts with targeted use of expensive, accurate sensors. This allows the deployment of sensors to build structured interpretations of situations. From these, an organization can meet mission-centered decision-making requirements with calibrated responses proportional to the likelihood of true detection and degree of threat.