Knowledge mining of unstructured information: application to cyber-domain
Information on cyber-related crimes, incidents, and conflicts is abundantly available in numerous open online sources. However, processing the large volumes and streams of data is a challenging task for the analysts and experts, and entails the need for newer methods and techniques. In this article we present and implement a novel knowledge graph and knowledge mining framework for extracting the relevant information from free-form text about incidents in the cyberdomain. The framework includes a machine learning based pipeline for generating graphs of organizations, countries, industries, products and attackers with a non-technical cyber-ontology. The extracted knowledge graph is utilized to estimate the incidence of cyberattacks on a given graph configuration. We use publicly available collections of real cyber-incident reports to test the efficacy of our methods. The knowledge extraction is found to be sufficiently accurate, and the graph-based threat estimation demonstrates a level of correlation with the actual records of attacks. In practical use, an analyst utilizing the presented framework can infer additional information from the current cyber-landscape in terms of risk to various entities and propagation of the risk heuristic between industries and countries.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
AISecKG: Knowledge Graph Dataset for Cybersecurity Education
Cybersecurity education is exceptionally challenging as it involves learning the complex attacks; tools and developing critical problem-solving skills to defend the systems. For a student or novice researcher in the cybe…
Active LearningKnowledge GraphsQuestion AnsweringRecommendation Systems+1Recognizing and Extracting Cybersecurtity-relevant Entities from Text
Cyber Threat Intelligence (CTI) is information describing threat vectors, vulnerabilities, and attacks and is often used as training data for AI-based cyber defense systems such as Cybersecurity Knowledge Graphs (CKG). T…
Entity LinkingKnowledge GraphsSelf-LearningWorld KnowledgeOpen-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+2Automated CVE Analysis: Harnessing Machine Learning In Designing Question-Answering Models For Cybersecurity Information Extraction
The vast majority of cybersecurity information is unstructured text, including critical data within databases such as CVE, NVD, CWE, CAPEC, and the MITRE ATT&CK Framework. These databases are invaluable for analyzing att…
Question AnsweringActionable Cyber Threat Intelligence using Knowledge Graphs and Large Language Models
Cyber threats are constantly evolving. Extracting actionable insights from unstructured Cyber Threat Intelligence (CTI) data is essential to guide cybersecurity decisions. Increasingly, organizations like Microsoft, Tren…
Knowledge GraphsLink PredictionPrompt Engineering