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EDESC-IDS:An Efficient Deep Embedded Subspace Clustering-Based Intrusion Detection System for the Internet of Vehicles

Lixing Tan Liusiyu Chen Yang Wang Zhenyu Song Zenan Lu

Computers, Materials & Continua2026，Vol.87Issue(5)：P.997-1020,24.

Computers, Materials & Continua2026，Vol.87Issue(5)：P.997-1020,24.DOI:10.32604/cmc.2026.075959

EDESC-IDS:An Efficient Deep Embedded Subspace Clustering-Based Intrusion Detection System for the Internet of Vehicles

Lixing Tan ¹Liusiyu Chen ²Yang Wang ²Zhenyu Song ²Zenan Lu³

作者信息

1. College of Information Engineering,Taizhou University,Taizhou,225300,China College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing,210016,China
2. College of Information Engineering,Taizhou University,Taizhou,225300,China
3. College of Information Engineering,Taizhou University,Taizhou,225300,China School of Computer Science,Fudan University,Shanghai,200433,China
折叠

摘要

关键词

Internet of vehicles/control area network/anomaly detection/unsupervised learning/deep embedded subspace clustering/extended convolutional autoencoder

分类

交通工程

引用本文复制引用

Lixing Tan,Liusiyu Chen,Yang Wang,Zhenyu Song,Zenan Lu..EDESC-IDS:An Efficient Deep Embedded Subspace Clustering-Based Intrusion Detection System for the Internet of Vehicles[J].Computers, Materials & Continua,2026,87(5):P.997-1020,24.

基金项目

supported by the National Natural Science Foundation of China(Grant No.62172292). （Grant No.62172292）

Computers, Materials & Continua

ISSN：1546-2218

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