Woo, S.,
Jo, H.J.,
Lee, D.H.,
A Practical Wireless Attack on the Connected Car and Security
Protocol for In-Vehicle CAN,
ITS(16), No. 2, April 2015, pp. 993-1006.
IEEE DOI
1504
Automotive engineering
BibRef
Woo, S.,
Jo, H.J.,
Kim, I.S.,
Lee, D.H.,
A Practical Security Architecture for In-Vehicle CAN-FD,
ITS(17), No. 8, August 2016, pp. 2248-2261.
IEEE DOI
1608
Automotive engineering
BibRef
Wu, W.,
Li, R.,
Xie, G.,
An, J.,
Bai, Y.,
Zhou, J.,
Li, K.,
A Survey of Intrusion Detection for In-Vehicle Networks,
ITS(21), No. 3, March 2020, pp. 919-933.
IEEE DOI
2003
Controller area network (CAN), cybersecurity,
in-vehicle network (IVN), intrusion detection system (IDS),
machine learning
BibRef
Aliwa, E.[Emad],
Rana, O.[Omer],
Perera, C.[Charith],
Burnap, P.[Peter],
Cyberattacks and Countermeasures for In-Vehicle Networks,
Surveys(54), No. 1, March 2021, pp. xx-yy.
DOI Link
2104
cybersecurity, CAN bus, intrusion detection systems
BibRef
Xie, G.Q.[Guo-Qi],
Yang, L.T.[Laurence T.],
Wu, W.[Wei],
Zeng, K.Y.[Ke-Yu],
Xiao, X.Z.[Xiang-Zhen],
Li, R.[Renfa],
Security Enhancement for Real-Time Parallel In-Vehicle Applications
by CAN FD Message Authentication,
ITS(22), No. 8, August 2021, pp. 5038-5049.
IEEE DOI
2108
Task analysis, Real-time systems, Bandwidth, Authentication,
Automotive engineering, Automobiles, Authentication,
security
BibRef
He, Y.C.[Yu-Chu],
Jia, Z.J.[Zhi-Juan],
Hu, M.S.[Ming-Sheng],
Cui, C.[Chi],
Cheng, Y.[Yage],
Yang, Y.Y.[Yan-Yan],
The Hybrid Similar Neighborhood Robust Factorization Machine Model
for Can Bus Intrusion Detection in the In-Vehicle Network,
ITS(23), No. 9, September 2022, pp. 16833-16841.
IEEE DOI
2209
Mathematical models, Data models, Intrusion detection,
Predictive models, Robustness, Computational modeling,
factorization machine
BibRef
Duan, X.[Xuting],
Yan, H.[Huiwen],
Tian, D.X.[Da-Xin],
Zhou, J.[Jianshan],
Su, J.[Jian],
Hao, W.[Wei],
In-Vehicle CAN Bus Tampering Attacks Detection for Connected and
Autonomous Vehicles Using an Improved Isolation Forest Method,
ITS(24), No. 2, February 2023, pp. 2122-2134.
IEEE DOI
2302
Anomaly detection, Computer hacking, Support vector machines,
Safety, Encryption, Autonomous vehicles, Authentication, data mass
BibRef
Derhab, A.[Abdelouahid],
Belaoued, M.[Mohamed],
Mohiuddin, I.[Irfan],
Kurniawan, F.[Fajri],
Khan, M.K.[Muhammad Khurram],
Histogram-Based Intrusion Detection and Filtering Framework for
Secure and Safe In-Vehicle Networks,
ITS(23), No. 3, March 2022, pp. 2366-2379.
IEEE DOI
2203
Intrusion detection, Feature extraction, Histograms, Safety,
Filtering, Wireless fidelity, Vehicle-to-everything, OCSVM
BibRef
Wang, K.[Kai],
Zhang, A.[Aiheng],
Sun, H.R.[Hao-Ran],
Wang, B.L.[Bai-Ling],
Analysis of Recent Deep-Learning-Based Intrusion Detection Methods
for In-Vehicle Network,
ITS(24), No. 2, February 2023, pp. 1843-1854.
IEEE DOI
2302
Intrusion detection, Biological system modeling,
Periodic structures, Deep learning, Adaptation models, Security,
vehicular networks
BibRef
Rajapaksha, S.[Sampath],
Kalutarage, H.[Harsha],
Al-Kadri, M.O.[M. Omar],
Petrovski, A.[Andrei],
Madzudzo, G.[Garikayi],
Cheah, M.[Madeline],
AI-Based Intrusion Detection Systems for In-Vehicle Networks:
A Survey,
Surveys(55), No. 11, February 2023, pp. xx-yy.
DOI Link
2303
machine learning, Controller Area Network (CAN),
Intrusion Detection System (IDS), automotive cybersecurity, in-vehicle network
BibRef
Zhang, J.[Jiangjiang],
Gong, B.[Bei],
Waqas, M.[Muhammad],
Tu, S.S.[Shan-Shan],
Chen, S.[Sheng],
Many-Objective Optimization Based Intrusion Detection for in-Vehicle
Network Security,
ITS(24), No. 12, December 2023, pp. 15051-15065.
IEEE DOI
2312
BibRef
Jeong, Y.[Yeonseon],
Kim, H.[Hyunghoon],
Lee, S.[Seyoung],
Choi, W.[Wonsuk],
Lee, D.H.[Dong Hoon],
Jo, H.J.[Hyo Jin],
In-Vehicle Network Intrusion Detection System Using CAN Frame-Aware
Features,
ITS(25), No. 5, May 2024, pp. 3843-3853.
IEEE DOI
2405
Feature extraction, Random forests, Decision trees, Standards,
Fuzzing, Boosting, Vehicles, Controller area network,
machine learning
BibRef
Cao, J.H.[Jin-Hui],
Di, X.Q.[Xiao-Qiang],
Liu, X.[Xu],
Li, J.Q.[Jin-Qing],
Li, Z.[Zhi],
Zhao, L.[Liang],
Hawbani, A.[Ammar],
Guizani, M.[Mohsen],
Anomaly Detection for In-Vehicle Network Using Self-Supervised
Learning With Vehicle-Cloud Collaboration Update,
ITS(25), No. 7, July 2024, pp. 7454-7466.
IEEE DOI
2407
Anomaly detection, Feature extraction, Predictive models, Data models,
Transformers, Intrusion detection, vehicle-cloud collaboration
BibRef
Huan, S.[Sha],
Zhang, X.Y.[Xiao-Yi],
Shang, W.L.[Wen-Li],
Cao, H.T.[Hai-Tao],
Li, H.[Heng],
Yang, Y.[Yuanjia],
Liu, W.[Wenbai],
T-Shaped CAN Feature Integration With Lightweight Deep Learning Model
for In-Vehicle Network Intrusion Detection,
ITS(25), No. 12, December 2024, pp. 21183-21196.
IEEE DOI
2412
Intrusion detection, Deep learning, Feature extraction, Entropy,
Security, Intelligent vehicles, Safety, Floods, deep learning (DL)
BibRef
Sun, H.[Heng],
Wang, J.Z.[Jing-Zhu],
Weng, J.[Jian],
Tan, W.H.[Wei-Hua],
KG-ID: Knowledge Graph-Based Intrusion Detection on In-Vehicle
Network,
ITS(26), No. 4, April 2025, pp. 4988-5000.
IEEE DOI Code:
WWW Link.
2504
Controller area networks, Feature extraction,
Intrusion detection, Protocols, Fingerprint recognition,
intrusion detection
BibRef
Chapter on New Unsorted Entries, and Other Miscellaneous Papers continues in
Direction of Arrival, DoA, Analysis .