Malware detection based on visualization of recombined API instruction sequence-Reference-Cited by-同舟云学术

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Malware detection based on visualization of recombined API instruction sequence

Published:2022-11-04 Issue:1 Volume:34 Page:2630-2651
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Yang Hongyu¹²,Zhang Yupei²,Zhang Liang³,Cheng Xiang⁴

Affiliation:

1. School of Safety Science and Engineering, Civil Aviation University of China, Tianjin, People’s Republic of China

2. School of Computer Science and Technology, Civil Aviation University of China, Tianjin, People’s Republic of China

3. School of Information, The University of Arizona, Tucson, AZ, USA

4. School of Information Engineering, Yangzhou University, Yangzhou, People’s Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2139353

Reference35 articles.

1. A Hybrid parallel deep learning model for efficient intrusion detection based on metric learning

2. LGMal: A Joint Framework Based on Local and Global Features for Malware Detection

3. Detection of Malicious Code Variants Based on Deep Learning

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Status and Outlook of Image-based Malware Detection Technology;2023 3rd International Symposium on Computer Technology and Information Science (ISCTIS);2023-07-07

2. Malware API Calls Detection Using Hybrid Logistic Regression and RNN Model;Applied Sciences;2023-04-27

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