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In-vehicle network Injection Attacks Detection Based on Feature Selection and Classification

Automotive Innovation 2024年第1期7卷 138-149页

作者： Haojie Ji Liyong Wang Hongmao Qin Yinghui Wang Junjie Zhang Biao Chen Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100192China State Key Laboratory of Advanced Design and Manufacturing for vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Hefei Innovation Research Institute Beihang UniversityHefei 230012China

Detecting abnormal data generated from cyberattacks has emerged as a crucial approach for identifying security threats within In-vehicle networks.The transmission of information through In-vehicle networks needs to follow specific data for-mats and communication protocols regulations.Typically,statistical algorithms are employed to learn these variation rules and facilitate the identification of abnormal data.However,the effectiveness of anomaly detection outcomes often falls short when confronted with highly deceptive In-vehicle network attacks.In this study,seven representative classification algorithms are selected to detect common In-vehicle network attacks,and a comparative analysis is employed to identify the most suitable and favorable detection method.In consideration of the communication protocol characteristics of In-vehicle networks,an optimal convolutional neural network(CNN)detection algorithm is proposed that uses data field characteristics and classifier selection,and its comprehensive performance is tested.In addition,the concept of Hamming distance between two adjacent packets within the In-vehicle network is introduced,enabling the proposal of an enhanced CNN algorithm that achieves robust detection of challenging-to-identify abnormal data.This paper also presents the proposed CNN classifica-tion algorithm that effectively addresses the issue of high false negative rate(FNR)in abnormal data detection based on the timestamp feature of data packets.The experimental results validate the efficacy of the proposed abnormal data detection algorithm,highlighting its strong detection performance and its potential to provide an effective solution for safeguarding the security of In-vehicle network information.

关键词： Classification algorithm Anomaly detection In-vehicle network Feature extraction Injecting attack

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A novel intrusion detection model for the CAN bus packet of In-vehicle network based on attention mechanism and autoencoder

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Digital Communications and networks 2023年第1期9卷 14-21页

作者： Pengcheng Wei Bo Wang Xiaojun Dai Li Li Fangcheng He School of Mathematics and Information Engineering Chongqing University of EducationChongqingChina School of Automation Chongqing University of Posts and TelecommunicationsChongqingChina Department of Modern Service Chongqing Energy Industry Technician CollegeChongqingChina College of Foreign Languages Literature Chongqing University of EducationChongqingChina

The attacks on in-vehicle Controller Area network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

关键词： Controller area network bus packet In-vehicle network Attention mechanism Autoencoder

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A Prompt Retransmission Method for In-vehicle network FlexRay

A Prompt Retransmission Method for In-Vehicle Network FlexRa...

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第36届中国控制会议

作者： Biao Liu Weiwei Bai Guangchuan Zhen School of Electrical Engineering Beijing Jiaotong University

ISBN: (纸本)9781538629185

FlexRay protocol has been developed as the de-facto industry standard for next generation in-vehicle communication with high bandwidth,time-triggered architecture and dual-channel redundancy.However,it does not define a mechanism to handle the transient errors,which is frequent on the common-used twisted wire cable.Thereby,FlexRay is hindered for the application in safety-critical communications.This paper presents a detailed Prompt ReTransmission Mechanism（PRTM） with acknowledgement and retransmission scheme to recovery the transient errors in the more safety-critical time-triggered messages.Considering the feasibility,failure probability reduction and bandwidth optimization,the amount of error messages permitted to be retransmitted in one cycle and the number of acknowledgement transmission is important for failure probability reduction;the schedule of the messages for acknowledgement and retransmission should be studied to optimize the bandwidth utilization.An example is used for demonstrating the effectiveness of PRTM,which can not only greatly reduce the messages failure probability but accomplish the retransmission within one cycle,together with an extra design cost and a small bandwidth waste.With PRTM,FlexRay would be notably promoted in safety-critical applications.

关键词： In-vehicle network FlexRay Prompt retransmission Transient errors recovery Messages failure probability

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ICAR Hybrid network: A Smart In-vehicle network for ScudWare

ICAR Hybrid Network: A Smart In-vehicle Network for ScudWare

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第一届建立和谐人机环境联合学术会议（HHME2005）

作者： Gao Zhigang+, Wu Zhaohui, Ye Ruizhi, Wu Qing College of Computer Science, Zhejiang University, Hangzhou 310027, China

Ubiquitous computing is a hotspot research field at present. The research about smart in-vehicle space is a main domain in ubiquitous computing. As cars play increasingly important role in people’s da

关键词： Smart Space In-vehicle network lazy response mechanism.

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Review of In‑vehicle Optical Fiber Communication Technology

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Automotive Innovation 2022年第3期5卷 272-284页

作者： Wenwei Wang Shiyao Yu Wanke Cao Kaidi Guo National Engineering Research Center of Electric vehicles Beijing Institute of Technology(BIT)BeijingChina Shenzhen Automotive Research Institute Beijing Institute of Technology(BIT)ShenzhenChina

With the continuous development of automotive intelligent networking and autonomous driving technologies,the number of in-vehicle electronic systems and applications is increasing rapidly.This change increases the amount of data to be transmitted in the vehicle and puts forward further requirements of higher speed and safety for in-vehicle communication.Traditional vehicle bus technologies are no longer sufficient to meet today’s high-speed transmission requirements,in which copper cables are used extensively,resulting in serious electromagnetic interference(EMI).vehicle optical fiber communication technology,besides greatly improving the data transmission rate,has the advantages of anti-EMI,reducing cable space and vehicle mass.This paper first presents the motivation of applying vehicle optical fiber communication technology and reviews the development history of vehicle optical fiber communication technology.Then,the paper researches the devel-opment trend of automotive electrical and electronic architecture(EEA),from distributed EEA to domain centralized EEA and zone-oriented EEA.Based on the discussion of the development trend of automotive EEA,an EEA based on vehicle optical fiber communication technology is proposed.Finally,the key points and future directions of vehicle optical fiber communication technology research are highlighted,including vehicle multi-mode optical fiber technology,vehicle optical fiber network protocol,and topology.

关键词： In-vehicle network Optical fiber communication Multi-mode optical fiber Electrical and electronic architecture

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Recent Trends of In-vehicle Time Sensitive networking Technologies, Applications and Challenges

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中国通信:英文版 2023年第11期20卷 30-55页

作者： Yanli Xu Jian Shang Hao Tang School of Information Engineering Shanghai Maritime UniversityShanghai 201306China

With the vigorous development of automobile industry,In-vehicle network is also constantly upgraded to meet data transmission requirements of emerging applications.The main transmission requirements are low latency and certainty especially for autonomous driving.Time sensitive networking(TSN)based on Ethernet gives a possible solution to these requirements.Previous surveys usually investigated TSN from a general perspective,which referred to TSN of various application fields.In this paper,we focus on the application of TSN to the In-vehicle networks.For In-vehicle networks,we discuss all related TSN standards specified by IEEE 802.1 work group up to now.We further overview and analyze recent literature on various aspects of TSN for automotive applications,including synchronization,resource reservation,scheduling,certainty,software and hardware.Application scenarios of TSN for In-vehicle networks are analyzed one by one.Since TSN of In-vehicle network is still at a very initial stage,this paper also gives insights on open issues,future research directions and possible solutions.

关键词： automobile industry deterministic transmission In-vehicle network low latency time sensitive networking(TSN)

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A Distribution-based Model for Electric/Electronic Architectures of Automotive

A Distribution-based Model for Electric/Electronic Architect...

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2015中国汽车工程学会年会

作者： Junting He Jianfeng Li Libo Zhang Automotive Electronics Department R＆D CenterChina FAW Co.Ltd.

In this paper,a distributed multi-level Electric/Electronic Architectures of Automotive is proposed,which is composed of a backbone network and multi-level local networks with the central coordinator controller as the controlling core.It achieves control command transmission and the implementing state information sharing through the backbone network and local area networks,and enhances network integration,flexibility and high scalability.The test sample vehicle verifies the feasibility,scalability and economy of the multi-level Electric/Electronic Architectures of Automotive.

关键词： distributed-based model electric/electronic architectures In-vehicle network coordination control network optimization

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