Privacy-Preserving and Gas-Efficient Car Service Record Management Using Adaptive User-Resilient CKKS Homomorphic Encryption and Blockchain
Received: 13 October 2025 | Revised: 10 November 2025 | Accepted: 21 November 2025 | Online: 9 February 2026
Corresponding author: G. Shree Devi
Abstract
Many car-selling and car-service websites have sprung up as a result of the automobile industry's quick digitization, offering consumers convenient access to vehicle details and transaction histories. Due to privacy and data management restrictions, these platforms typically show only the most basic information about an automobile, including its make, model, year of manufacture, mileage, price, and restricted ownership history, with Important service records, warranty claims, and part replacements typically left out. In addition to decreasing buyer transparency, the lack of thorough records makes it more difficult for automobile owners, dealers, and repair facilities to securely share data. Furthermore, data stored on centralized web servers is susceptible to loss of integrity, illegal changes, and data breaches. To overcome these obstacles, this study presents a unique method for the safe maintenance of comprehensive auto service records that combines blockchain technology with the AURA-CKKS homomorphic encryption scheme and the Brotli compression algorithm for storage optimization. The blockchain holds metadata, transaction logs, and Content Identifiers (CIDs) for traceability, while the InterPlanetary File System (IPFS) houses the compressed and encrypted data for decentralized and impenetrable storage. A Token-based Key Management System (TKMS) is utilized to securely distribute and maintain encryption keys among authorized stakeholders. The proposed architecture uses blockchain technology to ensure data immutability, AURA-CKKS encryption to maintain secrecy, and Brotli compression to reduce storage overhead, allowing all stakeholders to access verifiable and impenetrable vehicle histories while protecting data privacy. According to experimental results, the suggested framework decreases blockchain gas consumption by roughly 95% when compared to baseline raw on-chain storage, and by 94% compared to AURA-CKKS-based on-chain encryption. Brotli compression offers 43% reduction in data size. Additionally, in high-load circumstances, transaction confirmation time is decreased by 60%, query latency is reduced by 75%, and execution time is reduced by almost 55%. Due to adaptive bootstrapping and decentralized key verification, security testing reveals strong resilience (scores 4-5) against replay, Sybil, and key-theft attacks. These results confirm that the proposed architecture, combining AURA-CKKS, IPFS, TKMS, and blockchain, greatly improves computational efficiency, scalability, and privacy, providing a verifiable and tamper-proof vehicle-record management solution appropriate for next-generation automotive data ecosystems.
Keywords:
homomorphic encryption, AURA-CKKS, blockchain, token-based key management, interplanetary file systemDownloads
References
J. H. Cheon, A. Kim, M. Kim, and Y. Song, "Homomorphic Encryption for Arithmetic of Approximate Numbers," in Advances in Cryptology – ASIACRYPT 2017, vol. 10624, T. Takagi and T. Peyrin, Springer International Publishing, 2017, pp. 409–437. DOI: https://doi.org/10.1007/978-3-319-70694-8_15
J. H. Cheon, K. Han, A. Kim, M. Kim, and Y. Song, "Bootstrapping for Approximate Homomorphic Encryption," in Advances in Cryptology – EUROCRYPT 2018, vol. 10820, J. B. Nielsen and V. Rijmen, Springer International Publishing, 2018, pp. 360–384. DOI: https://doi.org/10.1007/978-3-319-78381-9_14
C. Gentry, S. Halevi, and N. P. Smart, "Homomorphic Evaluation of the AES Circuit," in Advances in Cryptology – CRYPTO 2012, vol. 7417, R. Safavi-Naini and R. Canetti, Springer Berlin Heidelberg, 2012, pp. 850–867. DOI: https://doi.org/10.1007/978-3-642-32009-5_49
C. Gentry, S. Halevi, and N. P. Smart, "Better Bootstrapping in Fully Homomorphic Encryption," in Public Key Cryptography – PKC 2012, vol. 7293, M. Fischlin, J. Buchmann, and M. Manulis, Springer Berlin Heidelberg, 2012, pp. 1–16. DOI: https://doi.org/10.1007/978-3-642-30057-8_1
T. V. T. Doan, M. L. Messai, G. Gavin, and J. Darmont, "A survey on implementations of homomorphic encryption schemes," The Journal of Supercomputing, vol. 79, no. 13, pp. 15098–15139, Sept. 2023. DOI: https://doi.org/10.1007/s11227-023-05233-z
C. Gouert, D. Mouris, and N. Tsoutsos, "SoK: New Insights into Fully Homomorphic Encryption Libraries via Standardized Benchmarks," Proceedings on Privacy Enhancing Technologies, vol. 2023, no. 3, pp. 154–172, July 2023. DOI: https://doi.org/10.56553/popets-2023-0075
F. Boemer, S. Kim, G. Seifu, F. D. M. de Souza, and V. Gopal, "Intel HEXL: Accelerating Homomorphic Encryption with Intel AVX512-IFMA52." arXiv, 2021. DOI: https://doi.org/10.1145/3474366.3486926
J. Benet, "IPFS - Content Addressed, Versioned, P2P File System." arXiv, 2014.
J. Alakuijala and Z. Szabadka, "Brotli Compressed Data Format," RFC7932, July 2016. DOI: https://doi.org/10.17487/RFC7932
Y. T. Jiang and H. M. Sun, "A Blockchain‐Based Vehicle Condition Recording System for Second‐Hand Vehicle Market," Wireless Communications and Mobile Computing, vol. 2021, no. 1, Jan. 2021, Art. no. 6623251. DOI: https://doi.org/10.1155/2021/6623251
S. El-Switi and M. Qatawneh, "Application of Blockchain Technology in Used Vehicle Market: A Review," in 2021 International Conference on Information Technology (ICIT), Amman, Jordan, July 2021, pp. 49–54. DOI: https://doi.org/10.1109/ICIT52682.2021.9491670
J. Yuan, W. Liu, J. Shi, and Q. Li, "Approximate homomorphic encryption based privacy-preserving machine learning: a survey," Artificial Intelligence Review, vol. 58, no. 3, Jan. 2025, Art. no. 82. DOI: https://doi.org/10.1007/s10462-024-11076-8
D. Dhinakaran, L. Srinivasan, S. M. Udhaya Sankar, and D. Selvaraj, "Quantum-based privacy-preserving techniques for secure and trustworthy internet of medical things an extensive analysis," Quantum Information & Computation, vol. 24, no. 3 & 4, pp. 227–266, Mar. 2024. DOI: https://doi.org/10.26421/QIC24.3-4-3
D. Dhinakaran, N. J. Kumar, N. P. Ponnuviji, and B. P. Kumar, "Safeguarding confidentiality and privacy in cloud-enabled healthcare systems with spectrasafe encryption and dynamic k-anonymity algorithm," Expert Systems with Applications, vol. 279, June 2025, Art. no. 127584. DOI: https://doi.org/10.1016/j.eswa.2025.127584
D. Dhinakaran, R. Ramani, S. E. Raja, and D. Selvaraj, "Enhancing clinical data security with the contextual polynomial-based data protection model (CPDPM)," Biomedical Signal Processing and Control, vol. 111, Jan. 2026, Art. no. 108329. DOI: https://doi.org/10.1016/j.bspc.2025.108329
D. Dhinakaran, L. Srinivasan, D. Selvaraj, and T. P. Anish, "A Novel Privacy Presevation of Healthcare Data with Information Entropy-Based Multi-Scheme Fully Homomorphic Encryption and Rivest Shamir Adleman Techniques," Biomedical Engineering: Applications, Basis and Communications, vol. 37, no. 04, Aug. 2025, Art. no. 2450060. DOI: https://doi.org/10.4015/S1016237224500601
D. Dhinakaran, G. Prabaharan, K. Valarmathi, S.M. U. Sankar, and R. Sugumar, "Safeguarding Privacy by utilizing SC-DℓDA Algorithm in Cloud-Enabled Multi Party Computation," KSII Transactions on Internet and Information Systems, vol. 19, no. 2, Feb. 2025. DOI: https://doi.org/10.3837/tiis.2025.02.014
"Vehicle History Reports," FAXVIN. https://www.faxvin.com/.
S. Yasmin and G. S. Devi, "An Adaptive User-Guided Resilient Approach for Dynamic Bootstrapping in Homomorphic Encryption," Engineering, Technology & Applied Science Research, vol. 15, no. 4, pp. 25984–25992, Aug. 2025. DOI: https://doi.org/10.48084/etasr.12045
Downloads
How to Cite
License
Copyright (c) 2025 S. Yasmin, G. Shree Devi
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
