Developing and Building Ontologies in Cyber Security
Cyber Security is one of the most arising disciplines in our modern society. We work on Cybersecurity domain and in this the topic we chose is Cyber Security Ontologies. In this we gather all latest and previous ontologies and compare them on the basis of different analyzing factors to get best of them. Reason to select this topic is to assemble different ontologies from different era of time. Because, researches that included in this SLR is mostly studied single ontology. If any researcher wants to study ontologies, he has to study every single ontology and select which one is best for his research. So, we assemble different types of ontology and compare them against each other to get best of them. A total 24 papers between years 2010-2020 are carefully selected through systematic process and classified accordingly. Lastly, this SLR have been presented to provide the researchers promising future directions in the domain of cybersecurity ontologies.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Towards an ontology of state actors in cyberspace
To improve cyber threat analysis practices in cybersecurity, I present a plan to build a formal ontological representation of state actors in cyberspace and of cyber operations. I argue that modelling these phenomena via…
CVE-LLM : Ontology-Assisted Automatic Vulnerability Evaluation Using Large Language Models
The National Vulnerability Database (NVD) publishes over a thousand new vulnerabilities monthly, with a projected 25 percent increase in 2024, highlighting the crucial need for rapid vulnerability identification to mitig…
ManagementCTINexus: Automatic Cyber Threat Intelligence Knowledge Graph Construction Using Large Language Models
Textual descriptions in cyber threat intelligence (CTI) reports, such as security articles and news, are rich sources of knowledge about cyber threats, crucial for organizations to stay informed about the rapidly evolvin…
ArticlesEntity Alignmentgraph constructionIn-Context Learning+2Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies
Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity system logs. However, current methodologies often struggle to identify and in…
Information ExtractionAutomated 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 Answering