TY - GEN
T1 - A General Construction Method of Cyber Security Knowledge Graph
AU - Qi, Yulu
AU - Gu, Zhaoquan
AU - Mei, Yangyang
AU - Lin, Kaihan
AU - Li, Aiping
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The corpora in cybersecurity knowledge base is characterized by multi-entity and weak relation. In order to solve the problem that entity extraction, entity links and entity disambiguation can lead to wrong knowledge, a knowledge graph construction method for security knowledge base is proposed. At the conceptual level, the cybersecurity ontology model and ontology-instance model are constructed based on the five-tuple model structure, and the ontology-instance model is classified and associated from the horizontal and vertical perspectives. In the data layer, the ontology features are combined with the named entity recognition model. While recognizing entities, the ontology-instance model is optimized. By comparing with other entity recognition models, the accuracy and efficiency of the optimized ontology-instance model are verified.
AB - The corpora in cybersecurity knowledge base is characterized by multi-entity and weak relation. In order to solve the problem that entity extraction, entity links and entity disambiguation can lead to wrong knowledge, a knowledge graph construction method for security knowledge base is proposed. At the conceptual level, the cybersecurity ontology model and ontology-instance model are constructed based on the five-tuple model structure, and the ontology-instance model is classified and associated from the horizontal and vertical perspectives. In the data layer, the ontology features are combined with the named entity recognition model. While recognizing entities, the ontology-instance model is optimized. By comparing with other entity recognition models, the accuracy and efficiency of the optimized ontology-instance model are verified.
KW - Cybersecurity knowledge graph
KW - Entity recognition
KW - Ontology model
KW - Rule reasoning
UR - https://www.scopus.com/pages/publications/85146436094
U2 - 10.1109/BESC57393.2022.9995070
DO - 10.1109/BESC57393.2022.9995070
M3 - 会议稿件
AN - SCOPUS:85146436094
T3 - Proceedings of the 2022 IEEE International Conference on Behavioural and Social Computing, BESC 2022
BT - Proceedings of the 2022 IEEE International Conference on Behavioural and Social Computing, BESC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Behavioural and Social Computing, BESC 2022
Y2 - 29 October 2022 through 31 October 2022
ER -