Next-Generation Security Entity Linkage: Harnessing the Power of Knowledge Graphs and Large Language

Daniel Alfasi, Tal Shapira, Anat Bremler-Barr

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With the continuous increase in reported Common Vulnerabilities and Exposures (CVEs), security teams are overwhelmed by vast amounts of data, which are often analyzed manually, leading to a slow and inefficient process. To address cybersecurity threats effectively, it is essential to establish connections across multiple security entity databases, including CVEs, Common Weakness Enumeration (CWEs), and Common Attack Pattern Enumeration and Classification (CAPECs). In this study, we introduce a new approach that leverages the RotatE [4] knowledge graph embedding model, initialized with embeddings from Ada language model developed by OpenAI [3]. Additionally, we extend this approach by initializing the embeddings for the relations.

Original languageEnglish
Title of host publicationProceedings of the 16th ACM International Conference on Systems and Storage, SYSTOR 2023
Pages150
Number of pages1
ISBN (Electronic)9781450399623
DOIs
StatePublished - 5 Jun 2023
Event16th ACM International Conference on Systems and Storage, SYSTOR 2023 - Haifa, Israel
Duration: 5 Jun 20237 Jun 2023

Publication series

NameProceedings of the 16th ACM International Conference on Systems and Storage, SYSTOR 2023

Conference

Conference16th ACM International Conference on Systems and Storage, SYSTOR 2023
Country/TerritoryIsrael
CityHaifa
Period5/06/237/06/23

Keywords

  • CAPEC
  • CVE
  • CWE
  • knowledge graph embedding

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering

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