Multi-level fine-tuning, data augmentation, and few-shot learning for specialized cyber threat intelligence-Reference-Cited by-同舟云学术

Multi-level fine-tuning, data augmentation, and few-shot learning for specialized cyber threat intelligence

Published:2023-11 Issue: Volume:134 Page:103430
ISSN:0167-4048
Container-title:Computers & Security
language:en
Short-container-title:Computers & Security

Author:

Bayer Markus^ORCID,Frey Tobias,Reuter Christian^ORCID

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference50 articles.

1. Cyber threat intelligence–issue and challenges;Abu;Indones. J. Electr. Eng. Comput. Sci.,2018

2. Follow the blue bird: a study on threat data published on Twitter;Alves,2020

3. Do not have enough data? Deep learning to the rescue!;Anaby-Tavor,2020

4. Data augmentation in natural language processing: a novel text generation approach for long and short text classifiers;Bayer;Int. J. Mach. Learn. Cybern.,2021

5. A survey on data augmentation for text classification;Bayer;ACM Comput. Surv.,2022

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