Intrusion Detection with Set-Valued Classification: Leveraging Dempster-Shafer Theory and Deep Learning-Reference-Cited by-同舟云学术

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Intrusion Detection with Set-Valued Classification: Leveraging Dempster-Shafer Theory and Deep Learning

Published:2023-12-08 Issue: Volume: Page:2155-2161
ISSN:
Container-title:2023 9th International Conference on Computer and Communications (ICCC)
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Author:

Wu Licheng¹,Xu Yue¹,Dai Zhicheng²,Wang Rui³,Chen Lunde²

Affiliation:

1. Shanghai University,School of Mechatronic Engineering and Automation,Shanghai,China,200444

2. Sino-European School of Technology of Shanghai University (UTSEUS), Shanghai University,Shanghai,China,200444

3. Beijing Jiaotong University,School of Computer and Information Technology,Beijing,China,100044

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10507208/10507251/10507447.pdf?arnumber=10507447

Reference18 articles.

1. Internet of Things in Industry: Research Profiling, Application, Challenges and Opportunities—A Review

2. Partial classification in the belief function framework

3. Efficient set-valued prediction in multi-class classification

4. An evidential classifier based on Dempster-Shafer theory and deep learning

5. Accelerated deep neural networks for enhanced Intrusion Detection System

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