Risk Modeling on Cyber Vulnerability Graphs

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/303912
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Bibliographical item details
Type: Examensarbete för masterexamen
Title: Risk Modeling on Cyber Vulnerability Graphs
Authors: Larsson, Simon
Abstract: 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.
Keywords: cyber security;graph kernels;Weisfeiler Lehman graph kernels;risk classification models
Issue Date: 2021
Publisher: Chalmers tekniska högskola / Institutionen för data och informationsteknik
URI: https://hdl.handle.net/20.500.12380/303912
Collection:Examensarbeten för masterexamen // Master Theses

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