Towards a relation extraction framework for cyber-security concepts
In order to assist security analysts in obtaining information pertaining to their network, such as novel vulnerabilities, exploits, or patches, information retrieval methods tailored to the security domain are needed. As labeled text data is scarce and expensive, we follow developments in semi-supervised Natural Language Processing and implement a bootstrapping algorithm for extracting security entities and their relationships from text. The algorithm requires little input data, specifically, a few relations or patterns (heuristics for identifying relations), and incorporates an active learning component which queries the user on the most important decisions to prevent drifting from the desired relations. Preliminary testing on a small corpus shows promising results, obtaining precision of .82.
Code (1)
Tasks
Active LearningInformation RetrievalRelationRelation ExtractionRetrievalSimilar Papers 제목 키워드 기반
TIJERE: A Novel Threat Intelligence Joint Extraction Model Based on Analyst Expert Knowledge
The extraction of entities and relationships from threat intelligence reports into structured formats, such as cybersecurity knowledge graphs, is essential for automated threat analysis, detection, and mitigation. Howeve…
Joint Entity and Relation ExtractionKnowledge GraphsRelExt: Relation Extraction using Deep Learning approaches for Cybersecurity Knowledge Graph Improvement
Security Analysts that work in a `Security Operations Center' (SoC) play a major role in ensuring the security of the organization. The amount of background knowledge they have about the evolving and new attacks makes a …
RelationRelation ExtractionOpen-CyKG: An Open Cyber Threat Intelligence Knowledge Graph
Instant analysis of cybersecurity reports is a fundamental challenge for security experts as an immeasurable amount of cyber information is generated on a daily basis, which necessitates automated information extraction …
Deep AttentionKnowledge GraphsNEROpen Information Extraction+2Towards a scalable AI-driven framework for data-independent Cyber Threat Intelligence Information Extraction
Cyber Threat Intelligence (CTI) is critical for mitigating threats to organizations, governments, and institutions, yet the necessary data are often dispersed across diverse formats. AI-driven solutions for CTI Informati…
Relation ExtractionZero-Shot LearningCybersecurity and Sustainable Development
Growing interdependencies between organizations lead them towards the creation of inter-organizational networks where cybersecurity and sustainable development have become one of the most important issues. The Environmen…
Management