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TIDL-IDS: A Time-Series Imaging and Deep Learning-Based IDS for Connected Autonomous Vehicles

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成果类型:
会议论文
作者:
Xia, Zhuoqun;Huang, Longfei;Tan, Jingjing;Jiang, Faqun;Hui, Zhenzhen
通讯作者:
Tan, JJ
作者机构:
[Tan, Jingjing; Huang, Longfei; Xia, Zhuoqun] Changsha Univ Sci & Technol, Changsha 410076, Peoples R China.
[Jiang, Faqun] Venustech Ltd Co, Beijing 100193, Peoples R China.
[Hui, Zhenzhen] Univ South China, Hengyang 421001, Peoples R China.
通讯机构:
[Tan, JJ ] C
Changsha Univ Sci & Technol, Changsha 410076, Peoples R China.
语种:
英文
关键词:
In-vehicle security;Intrusion detection;Deep convolutional neural network;MTF
期刊:
Lecture Notes in Computer Science
ISSN:
0302-9743
年:
2025
卷:
15258
页码:
269-285
会议名称:
27th International Conference on Information Security
会议论文集名称:
Lecture Notes in Computer Science
会议时间:
OCT 23-25, 2024
会议地点:
Arlington, VA
会议主办单位:
[Xia, Zhuoqun;Huang, Longfei;Tan, Jingjing] Changsha Univ Sci & Technol, Changsha 410076, Peoples R China.^[Jiang, Faqun] Venustech Ltd Co, Beijing 100193, Peoples R China.^[Hui, Zhenzhen] Univ South China, Hengyang 421001, Peoples R China.
主编:
Mouha, N Nikiforakis, N
出版地:
GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
出版者:
SPRINGER INTERNATIONAL PUBLISHING AG
ISBN:
978-3-031-75763-1; 978-3-031-75764-8
基金类别:
Scientific research project of Hunan Provincial Department of Education [22C0229]; Graduate Research Innovation Project of Changsha University of Science and Technology [CLKYCX24063]
机构署名:
本校为其他机构
摘要:
The popularity of Connected Autonomous Vehicles (CAVs) has led to improvements in the efficiency of the transportation system. Controller Area Network (CAN) is the standard communication protocol used in CAVs. However, the absence of effective security measures within CAN has resulted in vulnerabilities that can be exploited by attackers. To address this issue, we propose an Intrusion Detection System (IDS) using Time series Imaging and Deep Learning called TIDL-IDS. First, the CAN ID in the CAN frame is encoded as the Markov Transition Field (MTF) images to take into account the temporal char...

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