A Quantitative Methodology for Security Monitor Deployment

Abstract

Intrusion detection and forensic analysis techniques depend upon monitors to collect information about possible attacks. Since monitoring can be expensive, however, monitors must be selectively deployed to maximize their overall utility. This paper introduces a methodology both to evaluate monitor deployments quantitatively in terms of security goals and to deploy monitors optimally based on cost constraints. First, we define a model that describes the system assets, deployable monitors, and the relationship between generated data and intrusions. Then, we define a set of metrics that quantify the utility and richness of monitor data with respect to intrusion detection and the cost associated with deployment. Finally, we formulate a method using our model and metrics to determine the cost-optimal, maximum-utility placement of monitors. We present an enterprise Web service use case and illustrate how our metrics can be used to determine optimal monitor deployments for a set of common attacks on Web servers. Our approach is scalable, being able to compute within minutes optimal monitor deployments for systems with hundreds of monitors and attacks.