Risk Modeling on Cyber Vulnerability Graphs
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Typ
Examensarbete för masterexamen
Program
Publicerad
2021
Författare
Larsson, Simon
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Cyber security is a field which gets an increasing amount of attention. Record Future is a company providing services to aid and understand this field. An important part of their service is the Security Intelligence Graph (SIG), describing entities in the cyber threat world and how they relate to one and other. This master’s thesis
proposes a k-neighborhood graph approach for estimating security risks regarding Internet Domains which are present on the SIG. In order to classify Internet Domains their k-neighborhood graphs, on SIG, are mapped to a feature space using Weisfeiler-Lehman graph kernels. Two class and three class classifiers are implemented using support vector machines and logistic regression models. The results suggest that this approach works well for the two class classifier, where the models achieve accuracies around 0.96 and F1 scores around 0.89. The results are less promising for the multiclass models.
Beskrivning
Ämne/nyckelord
cyber security , graph kernels , Weisfeiler Lehman graph kernels , risk classification models