A Survey on Secure Computation Based on Homomorphic Encryption in Vehicular Ad Hoc Networks
Open accessAbstract
In vehicular ad hoc networks (VANETs), the security and privacy of vehicle data are core issues. In order to analyze vehicle data, they need to be computed. Encryption is a common method to guarantee the security of vehicle data in the process of data dissemination and computation. However, encrypted vehicle data cannot be analyzed easily and flexibly. Because homomorphic encryption supports computations of the ciphertext, it can completely solve this problem. In this paper, we provide a comprehensive survey of secure computation based on homomorphic encryption in VANETs. We first describe the related definitions and the current state of homomorphic encryption. Next, we present the framework, communication domains, wireless access technologies and cyber-security issues of VANETs. Then, we describe the state of the art of secure basic operations, data aggregation, data query and other data computation in VANETs. Finally, several challenges and open issues are discussed for future research.
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HE introduces prohibitive latency in large-scale traffic simulations due to polynomial-degree ciphertext operations, conflicting with sub-second response requirements for dynamic traffic management.
“HE, though theoretically robust, introduces prohibitive latency in large-scale traffic simulations due to polynomial-degree ciphertext operations, conflicting with sub-second response requirements for dynamic traffic management [2, 109, 132].”
From Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction (2025) · cites this paper as [132]
Section 4.5 (Challenges and Future Research Directions; page unavailable) says fully homomorphic encryption has excessively long multiplication times, making real-time communication in vehicular networks difficult. It does not establish prohibitive latency in large-scale traffic simulations, attribute that latency to polynomial-degree ciphertext operations, or specify sub-second requirements for dynamic traffic management. (LLM, conf=0.87)
Experimental — accuracy not yet measuredA few studies focused on specific PPML techniques within IoV applications, such as HE in VANETs, local-DP for securing IoV systems, BC-PPML in IoV, blockchain-enabled FL in IoV, blockchain for IoV, and FL in CAVs and ITS applications.
“A few studies focused on specific PPML techniques within IoV applications, such HE in vehicular ad hoc networks (VANETs) [132], local-DP for securing IoV systems [191], BC-PPML in IoV [56], blockchain-enabled FL in IoV [13], blockchain for IoV (discussed some aspects of BC-PPML) [151], and FL in CAVs [18] and ITS applications [185, 186].”
From Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction (2025) · cites this paper as [132]
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- Authors
- Sun, X., Yu, F. R., Zhang, P., Xie, W., & Peng, X.
- Affiliations
- Shenzhen University (CN)
- Carleton University (CA)
- Corresponding author
- Zhang, Peng
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2020-07-30
- Volume
- 20
- Issue
- 15
- Pages
- 4253
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC7435932
- OpenAlex
- W3045552396
- Cited by
- 23
- References
- 181
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 2 · 2023: 6 · 2022: 2 · 2021: 4
- FWCI
- 0.10
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Carleton University's Institutional Repository (MacOdrum Library, Carleton University) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China ([61702341], 61702342)
- China Postdoctoral Science Foundation (2019M653042)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Keywords
- homomorphic encryption, vehicular ad hoc networks, secure computation, vehicle data privacy, data aggregation, data query, VANET security, wireless access technologies
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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