Name
Abstract | ||
|---|---|---|
Attack graphs compute potential attack paths from a system configuration and known vulnerabilities of a system. Evidence graphs model intrusion evidence and dependencies among them. In this paper, we show how to map evidence graphs to attack graphs. This mapping is useful for application of attack graphs and evidence graphs for forensic analysis. In addition to helping to refine attack graphs by using known sets of dependent attack evidence, important probabilistic information contained in evidence graphs can be used to compute or refine potential attack success probabilities obtained from repositories like CVSS. Conversely, attack graphs can be used to add missing evidence or remove irrelevant evidence trails to build a complete evidence graph. We illustrated the mapping by using a database attack as a case study. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/WIFS.2012.6412636 | WIFS |
Keywords | DocType | ISSN |
forensic analysis,attack graphs,attack paths,probabilistic information,mapping algorithm,digital forensics,evidence graph mapping,attack success probabilities,dependent attack evidence,evidence graphs,database attack,graph theory,potential attack success probability,evidence probabilities,cvss,evidence graph model intrusion evidence,probability | Conference | 2157-4766 |
ISBN | Citations | PageRank |
978-1-4673-2286-7 | 3 | 0.45 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changwei Liu | 1 | 41 | 6.92 |
| Anoop Singhal | 2 | 576 | 168.78 |
| Duminda Wijesekera | 3 | 1464 | 141.54 |