Automatic extraction of named entities of cyber threats using a deep Bi-LSTM-CRF network

Author:

Kim Gyeongmin,Lee Chanhee,Jo Jaechoon,Lim HeuiseokORCID

Funder

Korea Creative Content Agency

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference38 articles.

1. Alzaidy R, Caragea C, Giles CL (2019) Bi-LSTM-CRF sequence labeling for keyphrase extraction from scholarly documents. In: The World Wide Web conference. ACM, pp 2551–2557

2. Bengio Y, Simard P, Frasconi P et al (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157–166

3. Bridges RA, Jones CL, Iannacone MD, Testa KM, Goodall JR (2013) Automatic labeling for entity extraction in cyber security. arXiv preprint arXiv:1308.4941

4. Character-Level V (2018) End-to-end recurrent neural network models for Vietnamese named entity recognition: word-level. In: Computational linguistics: 15th international conference of the Pacific Association for computational linguistics, PACLING 2017, Yangon, Myanmar, 16–18 Aug 2017, Revised Selected Papers, vol 781. Springer, p 219

5. Chismon D, Ruks M (2015) Threat intelligence: collecting, analysing, evaluating. MWR InfoSecurity Ltd, London

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