Towards a secure ITS: Overview, challenges and solutions
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In the context of IoV, several survey papers provided a broad overview of privacy and security challenges such as security in ITS, machine learning for vehicular network security, PPML for EVs, and security in 6G-enabled IoV.
“In the context of IoV, several survey papers provided a broad overview of privacy and security challenges such as security in intelligent transportation systems (ITS) [43], [129], machine learning for vehicular network security [134], PPML for electric vehicles (EVs) [121], and security in 6G-enabled IoV [98].”
From Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction (2025) · cites this paper as [129]
Vehicle-specific data, such as make, model, and usage, can increase the risk of targeted attacks.
“Vehicle-specific data, such as make, model, and usage, can also increase the risk of targeted attacks [43, 121, 129].”
From Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction (2025) · cites this paper as [129]
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Flagged first, then by citations
10 of the 262 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
IoB: Internet-of-batteries for electric Vehicles–Architectures, opportunities, and challenges
Li, H., Bin Kaleem, M., Liu, Z., Wu, Y., Liu, W., & Huang, Z. (2023) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2023.100128 · Cited by 95 · see citing works
An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs
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RetractedAbbasi, S., Khaledian, N., & Rahmani, A. M. (2024) · International Journal of Information Security · doi:10.1007/s10207-024-00878-0 · Cited by 15 · see citing works
Security Architecture for Swarms of Autonomous Vehicles in Smart Farming
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Intelligent Transport System based Blockchain to Preventing Routing Attacks
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RetractedSAMPARK: Secure and lightweight communication protocols for smart parking management
Limbasiya, T., Sahay, S. K., & Das, D. (2022) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2022.103381 · Cited by 7 · see citing works
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Advances of vehicular ad hoc network using machine learning approach
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“Vehicle-specific data, such as make, model, and usage, can also increase the risk of targeted attacks [43, 121, 129].”
Automatic generation of threat paths in internet of things‐based systems
Ramazanzadeh, M. A., Barzegar, B., & Motameni, H. (2022) · IET Communications · doi:10.1049/cmu2.12491 · Cited by 1 · see citing works
The Role of Machine Learning in Enhancing ADS-B Communication Security: A Comprehensive Review
Ahmed, W. (2025) · Premier Journal of Computer Science · doi:10.70389/pjcs.100008 · Cited by 1 · see citing works
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HBbITL: A Hierarchical Blockchain Based Secure Intelligent Traffic Light System
Chakraborty, S., & Majumder, A. (2025) · Automatic Control and Computer Sciences · doi:10.3103/s0146411625700154 · Cited by 1 · see citing works
A Review Paper of M-AODV Routing Protocol in VANET to Detect and Prevent Black Hole Attack
Jain, S., & Sen, N. K. (2022) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2022.46186 · Cited by 1 · see citing works
Nawawi, A. U., Dendyana, A. M., Prastyo, G. Y., Azhima, S. A. T. A., Hakim, N. F. A., & Ridwan, A. M. (2024) · International Conference on Wireless and Telematics (ICWT) · doi:10.1109/icwt62080.2024.10674718 · Cited by 1 · see citing works
A vehicle-to-infrastructure communication privacy protocolused BlockchainPreprint
Harrabi, S., Jaâfar, I. B., & Omrani, O. (2024) · Research Square · doi:10.21203/rs.3.rs-4078147/v1
Batita, S., Makni, A., & Amous, I. (2025) · The Computer Journal · doi:10.1093/comjnl/bxaf097
- Authors
- Sleem, L., Noura, H. N., & Couturier, R.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- American University of Beirut (LB)
- Corresponding author
- Sleem, Lama
- Venue
- Journal of Information Security and Applications
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 55
- Pages
- 102637
- ISSN
- 2214-2126 (ISSN-L)
- OpenAlex
- W3094279562
- Cited by
- 21
- References
- 262
- Citations by year
- 2025: 4 · 2024: 5 · 2023: 4 · 2022: 7 · 2021: 1
- FWCI
- 1.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of Information Security and Applications (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- American University of Beirut
- Maroun Semaan Faculty of Engineering and Architecture, American University of Beirut
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Engineering › Mechanical Engineering › IoT and GPS-based Vehicle Safety Systems
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- intelligent transportation systems, Internet of Vehicles, vehicular ad hoc networks, security attacks, privacy attacks, attack classification, security solutions, smart transportation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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