Tao Li1, Yongjin Hu1,*, Ankang Ju1, Zhuoran Hu2
CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 407-420, 2021, DOI:10.32604/cmc.2020.012023
Abstract Owing to the continuous barrage of cyber threats, there is a massive
amount of cyber threat intelligence. However, a great deal of cyber threat intelligence come from textual sources. For analysis of cyber threat intelligence, many
security analysts rely on cumbersome and time-consuming manual efforts. Cybersecurity knowledge graph plays a significant role in automatics analysis of cyber
threat intelligence. As the foundation for constructing cybersecurity knowledge
graph, named entity recognition (NER) is required for identifying critical
threat-related elements from textual cyber threat intelligence. Recently, deep neural network-based models have attained very good results in NER. However, the
performance of these… More >
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