Biblio

This paper presents the architecture of an end-to-end secu- rity testbed and security analytics framework, which aims to: i) understand real-world exploitation of known security vulnerabilities and ii) preemptively detect multi-stage at- tacks, i.e., before the system misuse. With the increasing number of security vulnerabilities, it is necessary for secu- rity researchers and practitioners to understand: i) system and network behaviors under attacks and ii) potential ef- fects of attacks to the target infrastructure. To safely em- ulate and instrument exploits of known vulnerabilities, we use virtualization techniques to isolate attacks in contain- ers, e.g., Linux-based containers or Virtual Machines, and to deploy monitors, e.g., kernel probes or network packet captures, across a system and network stack. To infer the evolution of attack stages from monitoring data, we use a probabilistic graphical model, namely AttackTagger, that represents learned knowledge of simulated attacks in our se- curity testbed and real-world attacks. Experiments are be- ing run on a real-world deployment of the framework at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign.