Structured-Anomaly Pursuit of Network Traffic via Corruption-Robust Low-Rank Tensor Decomposition-Reference-Cited by-同舟云学术

Structured-Anomaly Pursuit of Network Traffic via Corruption-Robust Low-Rank Tensor Decomposition

Published:2024-05 Issue:3 Volume:11 Page:2510-2523
ISSN:2327-4697
Container-title:IEEE Transactions on Network Science and Engineering
language:
Short-container-title:IEEE Trans. Netw. Sci. Eng.

Author:

Zeng Jiuzhen¹^ORCID,Yang Laurence T.¹^ORCID,Wang Chao²,Ruan Yiheng¹,Zhu Chenlu¹

Affiliation:

1. Hubei Key Laboratory of Distributed System Security, Hubei Engineering Research Center on Big Data Security, the School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

2. School of Electrical Engineering, University of South China, Hengyang, China

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Scientific Research Fund of Hunan Provincial Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488902/10510356/10479666.pdf?arnumber=10479666

Reference44 articles.

1. Tensor-Based Recurrent Neural Network and Multi-Modal Prediction With Its Applications in Traffic Network Management

2. A Survey of Intelligent Network Slicing Management for Industrial IoT: Integrated Approaches for Smart Transportation, Smart Energy, and Smart Factory

3. DisCOV: Distributed COVID-19 Detection on X-Ray Images With Edge-Cloud Collaboration

4. Minimizing Transient Congestion during Network Update in Data Centers

5. Mobile agent-based energy-aware and user-centric data collection in wireless sensor networks

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