SGER: Development of Linux Attack Scenarios in Support of Intrusion Detection in High Performance Clusters

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NSF-0352703Title: SGER: Development of Linux Attack Scenarios in Support of Intrusion Detection in High Performance ClustersPI: Rayford B. VaughnCluster and grid clusters based on the Linux operating system have become widely used computational resources in environments where large amounts of data have privacy, defense, reliability, or other security concerns. Cluster nodes exchange information through both TCP/IP and high-speed network fabrics that often bypass operating system controls. As clusters become ubiquitous with Internet connection commonplace, the services they deliver will likely place them at a greater risk for attacks or intentional misuse by insiders. Mississippi State University has been pursuing research in anomaly detection within High Performance Computing (HPC) networks since 2000. This work is currently sponsored by the National Science Foundation and the Department of Defense. One of the major challenges for research in anomaly detection within high performance networks is the dearth of data sets for evaluating performance. Such data sets are necessary to validate the efficacy of artificial intelligence techniques that are under development for the detection of anomalies resulting from misbehavior of users or programs or from faults, and for performance monitoring. Three different classes of attacks against clusters have been designed and simulated at MSU. This research will refine these attacks and introduce additional classes of attacks in HPC clusters and will archive data sets for general use by the research community looking at anomaly detection in HPC environments.