Abstract
The advancement of hacking techniques has extended the sophistication of cyberattacks. Facing evolving cyberattacks, security officers need to acquire information about cyberattacks to gain visibility into the fast-evolving threat landscape. This research proposes a novel threat intelligence summarization system that extracts critical information and produces a summary report. This study combines BERT and BiLSTM and proposes a hybrid word embedding model to capture the critical information in the corpus. The evaluation results show that the proposed system could summarize reports effectively.
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Chen, CM., Wang, YX., Cai, Z.X., Lee, B., Lai, G.H. (2022). Automatic Summarization of Critical Threat Intelligence Using Transfer Learning. In: Hsieh, SY., Hung, LJ., Klasing, R., Lee, CW., Peng, SL. (eds) New Trends in Computer Technologies and Applications. ICS 2022. Communications in Computer and Information Science, vol 1723. Springer, Singapore. https://doi.org/10.1007/978-981-19-9582-8_30
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DOI: https://doi.org/10.1007/978-981-19-9582-8_30
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