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cyberKG

A knowledge graph also referred to as a semantic network represents real-world networks of objects, situations, events, or concepts, and shows their relationships in relation to each other. Graph databases store this information and display it as graph structures, thus establishing the term "knowledge graph." The use of knowledge graphs has shown promise for several cybersecurity tasks, such as vulnerability assessment and threat analysis. This repository contains the source code of the cyberKG. This is an autonomously vulnerability knowledge graph based on the Labelled Property Graphs (LPGs). It was constructed using heterogeneous data sources.

Datasets

The datasets are available in the "Input/" directory.

Requirements

Python >= 3.6
Neo4j Desktop (Community Edition, version 1.5.7).
cwe2 library.
Cpe parser.
AllenNLP.
entity-fishing.
spaCy library.

How to run the code

You can run the code using The_code.ipynb.

Zenodo

You can see cyberKG Model.

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Python code to parse the CVE dataset and store it into neo4j database.

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