The probabilistic packet marking (PPM) algorithm is a promising way to discover the Internet map or an attack graph that the attack packets traversed during a distributed denial-of...
We optimally place intrusion detection system (IDS) sensors and prioritize IDS alerts using attack graph analysis. We begin by predicting all possible ways of penetrating a networ...
In recent years, the combinatorics of argumentation with arguments that can attack each other has been studied extensively. Especially, attack graphs (put in the focus of attentio...
In this paper, we position the correct way of using graphical models for enhancing cyber security analysis in enterprise networks. Graphical models can be powerful in representati...
We describe a framework for managing network attack graph complexity through interactive visualization, which includes hierarchical aggregation of graph elements. Aggregation coll...
While efficient graph-based representations have been developed for modeling combinations of low-level network attacks, relatively little attention has been paid to effective tech...
Steven Noel, Michael Jacobs, Pramod Kalapa, Sushil...
We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We self-multiply the clustered adjacency matrices to show atta...
Attack graphs are a valuable tool to network defenders, illustrating paths an attacker can use to gain access to a targeted network. Defenders can then focus their efforts on patc...
Abstract Attack graphs for large enterprise networks improve security by revealing critical paths used by adversaries to capture network assets. Even with simplification, current a...
In measuring the overall security of a network, a crucial issue is to correctly compose the measure of individual components. Incorrect compositions may lead to misleading results...