Error-correcting code embedding for confidential edge storage
Vikram V. Patelvikrampatel@gokuluniversity.ac.inFaculty of EngineeringGokul Global UniversitySidhpur, Gujarat, 384151, India0009-0006-4834-6766View full profile → , *Shobhit GoyalCorresponding authorshobhit.goyal@quantumeducation.inQuantum University Research CenterQuantum UniversityRoorkee, Uttarakhand, 247667, India0009-0009-2291-7614View full profile → , Puli LavanyaPuliLavanya2024@protonmail.comCentre for Multidisciplinary ResearchAnurag UniversityHyderabad, Telangana, 500080, India0009-0004-0880-2857View full profile → , Rupali Adhaurupalipadhau@gmail.comDepartment of Computer EngineeringIndira College of Engineering & ManagementPune, Maharashtra, 410506, IndiaView full profile → , Sushil Punwatkarsushil.punwatkar@rungta.orgDepartment of Computer Science and EngineeringRungta College of Engineering & TechnologyRungta International Skills UniversityBhilai, Chhattisgarh, 490024, IndiaView full profile → , Sakshi Pandeysakshi.pandey.orp@chitkara.edu.inCentre for Research Impact & OutcomeChitkara University Institute of Engineering and TechnologyChitkara UniversityRajpura, Punjab, 140401, India0009-0008-9966-2165View full profile →
* Corresponding author · click or hover a name for details
- Received:
- 01 Apr 2026
- Published Online:
- 31 Oct 2026
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JDMSC-3013
- Pages:
- 3839–3850
Abstract
At the network edge, confidential data storage requires a highly resilient noise, failure, and adversarial-access protection and low computation overhead. This paper introduces an error-correcting code (ECC) embedding framework that is specifically designed to be used in secure edge storage systems. The given solution combines lightweight coding schemes with dynamic redundancy assignment that provides data integrity and confidentiality with limited resources. To model the embedding and decoding processes, a mathematical model is developed which includes parity generation and efficient syndrome-based recovery. The framework facilitates dynamic error space and helps to reduce the risk of data leakage with the help of organized redundancy patterns. Experimental testing proves to be more reliable, has a shorter decoding time and is more resilient than traditional storage schemes.
Keywords
Subject Classifications
References
[1] E. Litvinov, H. Llumiguano, M. J. Santofimia, X. del Toro, F. J. Villanueva, and P. Rocha, “Code integrity and confidentiality: An active data approach for active and healthy ageing,” Sensors, vol. 23, no. 10, Art. no. 4794 (2023), doi: 10.3390/s23104794.
[2] M. B. Imtiaz and R. Kamran, “Mitigating transmission errors: A forward error correction-based framework for enhancing objective video quality,” Sensors, vol. 25, no. 11, Art. no. 3503 (2025), doi: 10.3390/s25113503.
[3] M. Usama and U. Yaman, “Embedding information into or onto additively manufactured parts: A review of QR codes, steganography and watermarking methods,” Materials, vol. 15, no. 7, Art. no. 2596 (2022), doi: 10.3390/ma15072596.
[4] A Bashir, N. Farooq, A. Pervaiz, and A. H. Mir, “Security comparison of NTRU-Encrypt and ECC in smart healthcare systems,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 29, no. 3, pp. 1249–1265 (2026), doi: 10.47974/JDMSC-2220.
[5] Z. Jiang, M. Zhang, W. Dong, C. Jiang, and F. Di, “Reversible data hiding algorithm in encrypted images based on adaptive median edge detection and matrix-based secret sharing,” Applied Sciences, vol. 14, no. 14, Art. no. 6267 (2024), doi: 10.3390/app14146267.
[6] H. Sultana, A. H. M. Kamal, G. Hossain, and M. A. Kabir, “A novel hybrid edge detection and LBP code-based robust image steganography method,” Future Internet, vol. 15, no. 3, Art. no. 108 (2023), doi: 10.3390/fi15030108.
[7] M. Chintamani, P. Paul, and L. Sa, “Compartmented multi-secret sharing scheme using elliptic curves,” Journal of Information and Optimization Sciences, vol. 47, no. 3, pp. 811–831 (2026), doi: 10.47974/JIOS-1362.
[8] C.-Y. Yang and J.-L. Wu, “Two-bit embedding histogram-prediction-error based reversible data hiding for medical images with smooth area,” Computers, vol. 10, no. 11, Art. no. 152 (2021), doi: 10.3390/computers10110152.
[9] V. Barbuto, C. Savaglio, M. Chen, and G. Fortino, “Disclosing edge intelligence: A systematic meta-survey,” Big Data and Cognitive Computing, vol. 7, no. 1, Art. no. 44 (2023), doi: 10.3390/bdcc7010044.
[10] C.-C. Lin, J. Lin, and C.-C. Chang, “Reversible data hiding for AMBTC compressed images based on matrix and Hamming coding,” Electronics, vol. 10, no. 3, Art. no. 281 (2021), doi: 10.3390/electronics10030281.
[11] Y.-S. Kim, C. Kim, and J.-S. No, “Overview of binary locally repairable codes for distributed storage systems,” Electronics, vol. 8, no. 6, Art. no. 596 (2019), doi: 10.3390/electronics8060596.
[12] R. C. Poonia, T. Singh, C. K. Rajashri, D. Mondal, and S. M. Patil, “Optimizing communication system security through comprehensive testing and intelligent network configurations,” Journal of Information and Optimization Sciences, vol. 47, no. 5-A, pp. 1709–1717 (2026), doi: 10.47974/JIOS-2261.
[13] R. Wang, G. Wu, Q. Wang, L. Yuan, Z. Zhang, and G. Miao, “Reversible data hiding in encrypted images using median edge detector and two’s complement,” Symmetry, vol. 13, no. 6, Art. no. 921 (2021), doi: 10.3390/sym13060921.
[14] S. G. Aarella, V. P. Yanambaka, S. P. Mohanty, and E. Kougianos, “Fortified-Edge 2.0: Advanced machine-learning-driven framework for secure PUF-based authentication in collaborative edge computing,” Future Internet, vol. 17, no. 7, Art. no. 272 (2025), doi: 10.3390/fi17070272.
