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Natural Language Processing (NLP) has recently gained wide attention in cybersecurity, particularly in Cyber Threat Intelligence (CTI) and cyber automation.
Bishop, C.M.: Training with Noise is Equivalent to Tikhonov Regularization. Neural Computation 7
1995
Earlier work this paper cites.
Shibata, Y., Kida, T., Fukamachi, S., Takeda, M., Shinohara, A., Shinohara, T., Arikawa, S.: Byte pair encoding: A text compression scheme that accelerates pattern matching (1999)
1999
Earlier work this paper cites.
Zur, R.M., Jiang, Y., Pesce, L.L., Drukker, K.: Noise injection for training artificial neural networks: A comparison with weight decay and early stopping. Medical physics 36
2009
Earlier work this paper cites.
Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the thirteenth international conference on artificial intelligence and statistics. pp. 249–256. JMLR Workshop and Conference Proceedings (2010)
2010
Earlier work this paper cites.
Socher, R., Perelygin, A., Wu, J., Chuang, J., Manning, C.D., Ng, A.Y., Potts, C.: Recursive deep models for semantic compositionality over a sentiment treebank. In: Proceedings of the 2013 conference on empirical methods in natural language processing. pp. 1631–1642 (2013)
2013
Earlier work this paper cites.
2016
Earlier work this paper cites.
Lim, S.K., Muis, A.O., Lu, W., Ong, C.H.: MalwareTextDB: A database for annotated malware articles. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). pp. 1557–1567. Association for Computational Linguistics, Vancouver, Canada (Jul 2017). https://doi.org/10.18653/v1/P17-1143, https://aclanthology.org/P17-1143
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. In: Advances in neural information processing systems. pp. 5998–6008 (2017)
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
Liu, X., Cheng, M., Zhang, H., Hsieh, C.J.: Towards robust neural networks via random self-ensemble. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 369–385 (2018)
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training (2018)
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Aghaei, E., Al-Shaer, E.: Threatzoom: neural network for automated vulnerability mitigation. In: Proceedings of the 6th Annual Symposium on Hot Topics in the Science of Security. pp. 1–3 (2019)
2019
Cited alongside, same era.
Aghaei, E., Serpen, G.: Host-based anomaly detection using eigentraces feature extraction and one-class classification on system call trace data. Journal of Information Assurance and Security (JIAS) 14
2019
Cited alongside, same era.
Dalton, A., Aghaei, E., Al-Shaer, E., Bhatia, A., Castillo, E., Cheng, Z., Dhaduvai, S., Duan, Q., Hebenstreit, B., Islam, M.M., et al.: Active defense against social engineering: The case for human language technology. In: Proceedings for the First International Workshop on Social Threats in Online Conversations: Understanding and Management. pp. 1–8 (2020)
2020
Later among the works it cites.
Lee, J., Yoon, W., Kim, S., Kim, D., Kim, S., So, C.H., Kang, J.: Biobert: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics 36
2020
Later among the works it cites.
Sajid, M.S.I., Wei, J., Alam, M.R., Aghaei, E., Al-Shaer, E.: Dodgetron: Towards autonomous cyber deception using dynamic hybrid analysis of malware. In: 2020 IEEE Conference on Communications and Network Security (CNS). pp. 1–9. IEEE (2020)
2020
Later among the works it cites.
Wang, C., Cho, K., Gu, J.: Neural machine translation with byte-level subwords. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 34, pp. 9154–9160 (2020)
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Ahn, H., Cha, S., Lee, D., Moon, T.: Uncertainty-based continual learning with adaptive regularization. Advances in Neural Information Processing Systems 32
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., et al.: Language models are unsupervised multitask learners. OpenAI blog 1
2019
Cited alongside, same era.
You, Z., Ye, J., Li, K., Xu, Z., Wang, P.: Adversarial noise layer: Regularize neural network by adding noise. In: 2019 IEEE International Conference on Image Processing (ICIP). pp. 909–913. IEEE (2019)
2019
Cited alongside, same era.
Aghaei, E., Shadid, W., Al-Shaer, E.: Threatzoom: Hierarchical neural network for cves to cwes classification. In: International Conference on Security and Privacy in Communication Systems. pp. 23–41. Springer (2020)
2020
Cited alongside, same era.
2020
Later among the works it cites.
Yin, J., Tang, M., Cao, J., Wang, H.: Apply transfer learning to cybersecurity: Predicting exploitability of vulnerabilities by description. Knowledge-Based Systems 210
2020
Later among the works it cites.
Ameri, K., Hempel, M., Sharif, H., Lopez Jr, J., Perumalla, K.: Cybert: Cybersecurity claim classification by fine-tuning the bert language model. Journal of Cybersecurity and Privacy 1
2021
Later among the works it cites.
Chen, Y., Ding, J., Li, D., Chen, Z.: Joint bert model based cybersecurity named entity recognition. In: 2021 The 4th International Conference on Software Engineering and Information Management. pp. 236–242 (2021)
2021
Later among the works it cites.
Das, S.S., Serra, E., Halappanavar, M., Pothen, A., Al-Shaer, E.: V2w-bert: A framework for effective hierarchical multiclass classification of software vulnerabilities. In: 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA). pp. 1–12. IEEE (2021)
2021
Later among the works it cites.
Gao, C., Zhang, X., Liu, H.: Data and knowledge-driven named entity recognition for cyber security. Cybersecurity 4
2021
Later among the works it cites.
Li, X., Yang, Z., Guo, P., Cheng, J.: An intelligent transient stability assessment framework with continual learning ability. IEEE Transactions on Industrial Informatics 17
2021
Later among the works it cites.
Zhou, S., Liu, J., Zhong, X., Zhao, W.: Named entity recognition using bert with whole world masking in cybersecurity domain. In: 2021 IEEE 6th International Conference on Big Data Analytics (ICBDA). pp. 316–320. IEEE (2021)
2021
Later among the works it cites.