16.7.2.7.41 Security in Vehicle Networks, Intrusions

Chapter Contents (Back)
Vehicle Networks. Networks. Intrusion Detection. VANET. The related:
See also Privacy in Vehicle Networks, VANET.
See also Edge Computing in Vehicle Networks, VANET.
See also In-Vehicle Network Intrusion. General networks:
See also Network Analysis, Wireless, Network Intrusion.

Sedjelmaci, H., Senouci, S.M., Ansari, N.,
Intrusion Detection and Ejection Framework Against Lethal Attacks in UAV-Aided Networks: A Bayesian Game-Theoretic Methodology,
ITS(18), No. 5, May 2017, pp. 1143-1153.
IEEE DOI 1705
Bayes methods, Games, Intrusion detection, Monitoring, Unmanned aerial vehicles, Bayesian game, intrusion detection system (IDS), intrusion ejection system (IES), unmanned aerial vehicles (UAVs), vehicular, networks BibRef

Liang, J., Lin, Q., Chen, J., Zhu, Y.,
A Filter Model Based on Hidden Generalized Mixture Transition Distribution Model for Intrusion Detection System in Vehicle Ad Hoc Networks,
ITS(21), No. 7, July 2020, pp. 2707-2722.
IEEE DOI 2007
Hidden Markov models, Vehicular ad hoc networks, Reliability, Intrusion detection, Safety, Computational modeling, filter model based on HgMTD model (FM-HgMTD) BibRef

Shu, J.G.[Jian-Gang], Zhou, L.[Lei], Zhang, W.Z.[Wei-Zhe], Du, X.J.[Xiao-Jiang], Guizani, M.[Mohsen],
Collaborative Intrusion Detection for VANETs: A Deep Learning-Based Distributed SDN Approach,
ITS(22), No. 7, July 2021, pp. 4519-4530.
IEEE DOI 2107
Intrusion detection, Vehicular ad hoc networks, Collaboration, Servers, Monitoring, Machine learning, generative adversarial networks BibRef

Xie, G.Q.[Guo-Qi], Yang, L.T.[Laurence T.], Yang, Y.[Yuanda], Luo, H.B.[Hai-Bo], Li, R.[Renfa], Alazab, M.[Mamoun],
Threat Analysis for Automotive CAN Networks: A GAN Model-Based Intrusion Detection Technique,
ITS(22), No. 7, July 2021, pp. 4467-4477.
IEEE DOI 2107
Automotive engineering, Generative adversarial networks, Intrusion detection, Deep learning, Security, Training, threat analysis BibRef

dos Santos-Roque, A.[Alexandre], Jazdi, N.[Nasser], de Freitas, E.P.[Edison Pignaton], Pereira, C.E.[Carlos Eduardo],
A Fault Modeling Based Runtime Diagnostic Mechanism for Vehicular Distributed Control Systems,
ITS(23), No. 7, July 2022, pp. 7220-7232.
IEEE DOI 2207
Protocols, Degradation, Runtime, Automotive engineering, Decentralized control, Data models, Task analysis, vehicular control systems BibRef

Taguchi, S.[Shun], Yoshimura, T.[Takayoshi],
Online Estimation and Prediction of Large-Scale Network Traffic From Sparse Probe Vehicle Data,
ITS(23), No. 7, July 2022, pp. 7233-7243.
IEEE DOI 2207
Roads, Probes, Data models, Data assimilation, Predictive models, Neural networks, Network topology, Data assimilation, traffic speed prediction BibRef

Islam, R.[Riadul], Refat, R.U.D.[Rafi Ud Daula], Yerram, S.M.[Sai Manikanta], Malik, H.[Hafiz],
Graph-Based Intrusion Detection System for Controller Area Networks,
ITS(23), No. 3, March 2022, pp. 1727-1736.
IEEE DOI 2203
Protocols, Autonomous vehicles, Fabrication, Intrusion detection, Feature extraction, Cyberattack, Controller area network, security, graph-theory BibRef

Yu, Y.T.[Yan-Tao], Zeng, X.[Xin], Xue, X.P.[Xiao-Ping], Ma, J.X.[Jing-Xiao],
LSTM-Based Intrusion Detection System for VANETs: A Time Series Classification Approach to False Message Detection,
ITS(23), No. 12, December 2022, pp. 23906-23918.
IEEE DOI 2212
Time series analysis, Safety, Deep learning, Data models, Visualization, Vehicular ad hoc networks, Vehicles, long short-term memory model (LSTM) BibRef

Oseni, A.[Ayodeji], Moustafa, N.[Nour], Creech, G.[Gideon], Sohrabi, N.[Nasrin], Strelzoff, A.[Andrew], Tari, Z.[Zahir], Linkov, I.[Igor],
An Explainable Deep Learning Framework for Resilient Intrusion Detection in IoT-Enabled Transportation Networks,
ITS(24), No. 1, January 2023, pp. 1000-1014.
IEEE DOI 2301
Internet of Things, Security, Intrusion detection, Protocols, Deep learning, Safety, Explainable AI, network intrusion detection, Internet of Vehicles (IoV) BibRef

Ahmed, U.[Usman], Lin, J.C.W.[Jerry Chun-Wei], Srivastava, G.[Gautam], Yun, U.[Unil], Singh, A.K.[Amit Kumar],
Deep Active Learning Intrusion Detection and Load Balancing in Software-Defined Vehicular Networks,
ITS(24), No. 1, January 2023, pp. 953-961.
IEEE DOI 2301
Sensors, Load modeling, Load management, Task analysis, Servers, Resource management, Optimization, smart city application BibRef

Anbalagan, S.[Sudha], Raja, G.[Gunasekaran], Gurumoorthy, S.[Sugeerthi], Suresh, R.D.[R. Deepak], Dev, K.[Kapal],
IIDS: Intelligent Intrusion Detection System for Sustainable Development in Autonomous Vehicles,
ITS(24), No. 12, December 2023, pp. 15866-15875.
IEEE DOI 2312
BibRef

Kong, X.Y.[Xiang-Yu], Yang, G.H.[Guang-Hong],
Anti-Watermarking Stealthy Deception Attacks Against Networked Unmanned Surface Vehicles,
ITS(25), No. 9, September 2024, pp. 12835-12840.
IEEE DOI 2409
Watermarking, Detectors, Wireless networks, System performance, State estimation, Intelligent transportation systems, Uplink, auxiliary estimator BibRef

Zheng, G.[Guhan], Ni, Q.[Qiang], Lu, Y.[Yang],
Privacy-Aware Anomaly Detection and Notification Enhancement for VANET Based on Collaborative Intrusion Detection System,
ITS(25), No. 12, December 2024, pp. 21172-21182.
IEEE DOI 2412
Vehicular ad hoc networks, Intrusion detection, Privacy, Blockchains, Roads, Games, Trust management, Nash equilibrium, Nash equilibrium BibRef

Aljabri, W.[Wael], Hamid, M.A.[Md. Abdul], Mosli, R.[Rayan],
Lightweight and Adaptive Data-Driven Intrusion Detection System for Autonomous Vehicles,
ITS(26), No. 2, February 2025, pp. 2282-2292.
IEEE DOI 2502
Accuracy, Computer crime, Vehicle-to-everything, Training, Long short term memory, Automobiles, Safety, Intrusion detection, car-hacking BibRef

Huang, Y.F.[Yun-Fan], Ma, M.[Maode],
AILL-IDS: An Automatic Incremental Lifetime Learning Intrusion Detection System for Vehicular Ad Hoc Networks,
ITS(26), No. 2, February 2025, pp. 2669-2678.
IEEE DOI 2502
Vehicular ad hoc networks, Vehicle dynamics, Data models, Adaptation models, Accuracy, Incremental learning, vehicle ad hoc network BibRef

Ahmed, S.[Shafiq], Anisi, M.H.[Mohammad Hossein],
AIDAS: AI-Enhanced Intrusion Detection and Authentication for Autonomous Vehicles,
ITS(26), No. 8, August 2025, pp. 12548-12557.
IEEE DOI 2508
Authentication, Security, Cryptography, Autonomous vehicles, Accuracy, Protocols, Artificial intelligence, Vectors, smart grid BibRef

Hakeem, S.A.A.[Shimaa A. Abdel], Kim, H.[HyungWon],
Advancing Intrusion Detection in V2X Networks: A Comprehensive Survey on Machine Learning, Federated Learning, and Edge AI for V2X Security,
ITS(26), No. 8, August 2025, pp. 11137-11205.
IEEE DOI 2508
Vehicle-to-everything, Security, Surveys, Intrusion detection, Computational modeling, Federated learning, Real-time systems, 5G/6G security BibRef

Gupta, N.[Nishu], Malladi, R.[Ravishankar], Naganjaneyulu, S.[Satuluri], Balhara, S.[Surjeet],
Optimized Attention Induced Multi Head Convolutional Neural Network for Intrusion Detection Systems in Vehicular Ad Hoc Networks,
ITS(26), No. 8, August 2025, pp. 11957-11966.
IEEE DOI 2508
Vehicular ad hoc networks, Accuracy, Anomaly detection, Security, Intrusion detection, Adaptation models, Real-time systems, sensor networks BibRef

Li, X.M.[Xue-Mei], Fu, H.[Huirong],
SecureBERT and Llama 2 Empowered Control Area Network Intrusion Detection and Classification,
ITS(26), No. 10, October 2025, pp. 15248-15263.
IEEE DOI 2511
Adaptation models, Transformers, Intrusion detection, Training, Hidden Markov models, Computer security, Computer architecture, vehicle cybersecurity BibRef

Pooranian, Z.[Zahra], Taheri, R.[Rahim], Martinelli, F.[Fabio],
LFD-IDS: Bagging-Based Data Poisoning Attacks Against Cyberattack Detection in Connected Vehicle,
ITS(26), No. 10, October 2025, pp. 16800-16810.
IEEE DOI 2511
Cloud computing, Training, Temperature sensors, Cyberattack, Computer architecture, Accuracy, Connected vehicles, Training data, intrusion detection systems (IDS) BibRef

Jin, L.[Li], Zha, J.W.[Jia-Wei], Zhang, G.[Guoan], Zhu, H.[Hao], Duan, W.[Wei], Sun, Q.[Qiang], Zhang, J.Y.[Jia-Yi], Ho, P.H.[Pin-Han],
Intrusion Detection for Future ITS: Integrated Knowledge Graph and Artificial Intelligence,
ITS(26), No. 10, October 2025, pp. 14680-14689.
IEEE DOI 2511
Knowledge graphs, Intrusion detection, Feature extraction, Accuracy, Machine learning, Botnet, Overfitting, SHAP BibRef


Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Privacy in Vehicle Networks, VANET .


Last update:Nov 10, 2025 at 14:27:42