DeepAG: Attack Graph Construction and Threats Prediction With Bi-Directional Deep Learning-Reference-Cited by-同舟云学术

DeepAG: Attack Graph Construction and Threats Prediction With Bi-Directional Deep Learning

Author:

Li Teng¹^ORCID,Jiang Ya²^ORCID,Lin Chi³^ORCID,Obaidat Mohammad S.⁴^ORCID,Shen Yulong²^ORCID,Ma Jianfeng¹^ORCID

Affiliation:

1. School of Cyber Engineering, Xidian University, Xi'an, Shaanxi, China

2. School of Computer Science and Technology, Xidian University, Xi'an, Shaanxi, China

3. School of Software Technology, Dalian University of Technology, Dalian, Liaoning, China

4. College of Computing and Informatics, University of Sharjah, Sharjah, UAE

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Shaanxi University Science and Technology Association Youth Talent Promotion

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

Reference52 articles.

1. GPT-3: Language models are few-shot learners;brown;Adv in Neural Info Proc Syst,2020

2. A hybrid structured deep neural network with Word2Vec for construction accident causes classification;zhang;Int J Constr Manag,2019

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