Mathematics and statistics

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Visible to the public EAGER: Collaborative: Algorithmic Framework for Anomaly Detection in Interdependent Networks

Modern critical infrastructure relies on successful interdependent function among many different types of networks. For example, the Internet depends on access to the power grid, which in turn depends on the power-grid communication network and the energy production network. For this reason, network science researchers have begun examining the robustness of critical infrastructure as a network of networks, or a multilayer network. Research in network anomaly detection systems has focused on single network structures (specifically, the Internet as a single network).

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Visible to the public TWC: Small: Understanding Network Level Malicious Activities: Classification, Community Detection and Inference of Security Interdependence

This goal of this project is development of a formal method to quantitatively assess the security posture of large networks and assign them a numeric score. Large networks are made up of a collection of individual machines, which exhibit more stable behavior and features as a group than at the IP level, where each host is inspected separately. Networks at an aggregate level thus carry more predictive power, enabling a more robust and accurate policy design.