Visible to the public Tracking the Bad Guys: An Efficient Forensic Methodology to Trace Multi-Step Attacks Using Core Attack Graphs

TitleTracking the Bad Guys: An Efficient Forensic Methodology to Trace Multi-Step Attacks Using Core Attack Graphs
Publication TypeConference Paper
Year of Publication2017
AuthorsBarrere, M., Steiner, R. V., Mohsen, R., Lupu, E. C.
Conference Name2017 13th International Conference on Network and Service Management (CNSM)
KeywordsAlgorithm design and analysis, Attack Graphs, attack paths, bad guys tracking, compact representation, complex networks, Complexity theory, composability, Computer crime, core attack graph, core graphs, digital forensics, forensic evaluation threshold, forensic investigators, forensic methodology, Forensics, graph theory, information retrieval, Metrics, multistep attacks, network forensic analysis, network privileges, network size, network targets, network theory (graphs), network topologies, pubcrawl, resilience, Resiliency, security, standard logical attack graphs, Standards, summarised information retrieval, Tools
Abstract

In this paper, we describe an efficient methodology to guide investigators during network forensic analysis. To this end, we introduce the concept of core attack graph, a compact representation of the main routes an attacker can take towards specific network targets. Such compactness allows forensic investigators to focus their efforts on critical nodes that are more likely to be part of attack paths, thus reducing the overall number of nodes (devices, network privileges) that need to be examined. Nevertheless, core graphs also allow investigators to hierarchically explore the graph in order to retrieve different levels of summarised information. We have evaluated our approach over different network topologies varying parameters such as network size, density, and forensic evaluation threshold. Our results demonstrate that we can achieve the same level of accuracy provided by standard logical attack graphs while significantly reducing the exploration rate of the network.

URLhttps://ieeexplore.ieee.org/document/8256038/
DOI10.23919/CNSM.2017.8256038
Citation Keybarrere_tracking_2017