<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="host-etal-2023-constructing">
    <titleInfo>
        <title>Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Anders</namePart>
        <namePart type="family">Høst</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Pierre</namePart>
        <namePart type="family">Lison</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Leon</namePart>
        <namePart type="family">Moonen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-05</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Tanel</namePart>
            <namePart type="family">Alumäe</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mark</namePart>
            <namePart type="family">Fishel</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>University of Tartu Library</publisher>
            <place>
                <placeTerm type="text">Tórshavn, Faroe Islands</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Knowledge graphs have shown promise for several cybersecurity tasks, such as vulnerability assessment and threat analysis. In this work, we present a new method for constructing a vulnerability knowledge graph from information in the National Vulnerability Database (NVD). Our approach combines named entity recognition (NER), relation extraction (RE), and entity prediction using a combination of neural models, heuristic rules, and knowledge graph embeddings. We demonstrate how our method helps to fix missing entities in knowledge graphs used for cybersecurity and evaluate the performance.</abstract>
    <identifier type="citekey">host-etal-2023-constructing</identifier>
    <location>
        <url>https://aclanthology.org/2023.nodalida-1.40</url>
    </location>
    <part>
        <date>2023-05</date>
        <extent unit="page">
            <start>386</start>
            <end>391</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database
%A Høst, Anders
%A Lison, Pierre
%A Moonen, Leon
%Y Alumäe, Tanel
%Y Fishel, Mark
%S Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
%D 2023
%8 May
%I University of Tartu Library
%C Tórshavn, Faroe Islands
%F host-etal-2023-constructing
%X Knowledge graphs have shown promise for several cybersecurity tasks, such as vulnerability assessment and threat analysis. In this work, we present a new method for constructing a vulnerability knowledge graph from information in the National Vulnerability Database (NVD). Our approach combines named entity recognition (NER), relation extraction (RE), and entity prediction using a combination of neural models, heuristic rules, and knowledge graph embeddings. We demonstrate how our method helps to fix missing entities in knowledge graphs used for cybersecurity and evaluate the performance.
%U https://aclanthology.org/2023.nodalida-1.40
%P 386-391

Markdown (Informal)

[Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database](https://aclanthology.org/2023.nodalida-1.40) (Høst et al., NoDaLiDa 2023)

• Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database (Høst et al., NoDaLiDa 2023)

ACL

• Anders Høst, Pierre Lison, and Leon Moonen. 2023. Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database. In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), pages 386–391, Tórshavn, Faroe Islands. University of Tartu Library.