Lattice-Based Post-Quantum Cryptography Techniques as a Reliable Security Procedure to Build a Secure Mobile Health System
DOI:
https://doi.org/10.46610/IJDTNSS.2026.v02i02.00Keywords:
DEFLATE Compression, IPFS, mHealth, NTRUSign, Post-quantum cryptography, Quantum threatsAbstract
Numerous organizations, including medical establishments, engage with an ongoing, extensive flow of individuals of varying ages year-round. This leads to the accumulation of extensive patient information, encompassing diagnostic test outcomes, medical imaging like X-rays and CT scans, along with several other data types. Considering the paramount significance of this data, it is susceptible to illicit access by adversaries who may attempt to modify physician-recommended therapies or alter patient appointment arrangements. Mobile health (mHealth) organizations face difficulties due to quantum threats, where advanced computing systems are employed to compromise the security of conventional infrastructures. Strategies have been developed to mitigate these dangers, which pose considerable hazards to institutional security, including post-quantum cryptography. This method, which is resilient to both classical and quantum threats, is founded on lattice-based cryptography. It is defined by mathematical intricacy that renders it challenging for quantum computers to decipher. This paper introduces a security system designed to safeguard mHealth data through the use of technologies such as the Post-Quantum Giophantus Encryption, Post-Quantum-NTRUSign (pqNTRUSign), DEFLATE data compression, and InterPlanetary File System (IPFS). The system was analyzed for both security and performance. The results obtained were as follows: the average execution time was approximately 73.643 milliseconds, the average throughput was approximately 10.40 MB/sec operations per second, the latency time was approximately 0.0074 milliseconds per record, and the communication complexity was 218,293 bytes. The suggested system constitutes a satisfactory alternative in comparison to earlier systems.
References
A. Ahmad and S. Jagatheswari, “Lattice-based three party authenticated key agreement scheme in Medical IoT for post-quantum environment,” in IEEE Access, vol. 12, pp. 157247–157259.
E. W. Abood, A. A. Yassin, Z. A. Abduljabbar, V. O. Nyangaresi, and A. H. Ali, “Provably lightweight and secure IoHT scheme with post-quantum cryptography and fog computing: A comprehensive scheme for healthcare system,” MethodsX, vol. 15, Dec. 2025.
Z. G. Al-Mekhlaf et al., “A quantum-resilient lattice-based security framework for Internet of medical things in healthcare systems,” Journal of King Saud University Computer and Information Sciences, vol. 37, Jul. 2025.
A. Raad, M. A. Gabbar, and M. M. Zahra, “Quantum and lattice-based hybrid cryptosystem for secure wireless body sensor networks in medical applications,” SN Computer Science, vol. 6, Nov. 2025.
S. Prajapat, G. Thakur, P. Kumar, A. K. Das, S. S. Jamal, and W. Susilo, “Designing lattice-enabled group authentication scheme based on post-quantum computing in healthcare applications,” Computers and Electrical Engineering, vol. 123, Apr. 2025.
T. G. Tregi and M. Al-Zubaidie, “Lightweight quantum signatures for smart city data integrity and accuracy,” 2025 3rd International Conference on Business Analytics for Technology and Security (ICBATS), Dubai, United Arab Emirates, 2025, pp. 1–7.
M. H. Al-Zubaidie and T. G. Tregi, “Securing smart cities data using quantum techniques and preventing the alteration of citizens’ information,” in AI, Cybersecurity, and Next-Generation Mobility in Smart Cities. IGI Global Scientific Publishing, 2026, pp. 199–234.
M. H. Al-Zubaidie and T. G. Tregi, “Protecting data of power stations in smart cities using quantum-resistant and zero-knowledge proof,” in Securing Smart Cities Through Modern Cryptography Technologies. IGI Global Scientific Publishing, 2026, pp. 225–262.
M. Al-Zubaidie and T. G. Tregi, “A quantum resilient security system for smart power grid data: combining Kyber, FALCON, and zero-knowledge proofs against quantum threats,” Applied Data Science and Analysis, vol. 2025, pp. 201–220, Nov. 2025.
T. G. Tregi and M. Al-Zubaidie, “Enhancing traffic data security in smart cities using optimized quantum-based digital signatures and privacy-preserving techniques,” Mesopotamian Journal of CyberSecurity, vol. 5, no. 1, 2025.
L. Nurgalieva, D. O’Callaghan and G. Doherty, “Security and privacy of mHealth Applications: A scoping review,” in IEEE Access, vol. 8, pp. 104247–104268, 2020.
R. Kuvonchbek, A. K. Azamzade, S. Makhmudov, T. Bekzod, and S. Mamasoliyev, “Ensuring the security of transactions in financial information networks based on modern symmetric cryptosystems in the digital economy,” in Internet of Things, Smart Spaces, and Next Generation Networks and Systems, Y. Koucheryavy and A. Aziz, Eds., Cham, Switzerland: Springer, 2025, pp. 145–162.
R. K C, S. S K, G. M and A. S, “Performance evaluation of quantum-resistant algorithm in blockchain using FALCON,” 2025 3rd International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), Erode, India, 2025, pp. 1748–1753.
V. Wood, “What is the IPFS (InterPlanetary File System)? How it works and how to use IPFS?” GetBlock.io, Sep. 4, 2023.
K. Akiyama, Y. Goto, S. Okumura, T. Takagi, K. Nuida, and G. Hanaoka, “A public-key encryption scheme based on non-linear indeterminate equations,” in Selected Areas in Cryptography—SAC 2017: 24th International Conference, Revised Selected Papers, C. Adams and J. Camenisch, Eds., Cham, Switzerland: Springer, 2018, pp. 215–234.
M. W. Legernæs, “On the development and standardisation of post-quantum cryptography: A synopsis of the NIST post-quantum cryptography standardisation process, its incentives, and submissions,” M.S. thesis, Norwegian University of Science and Technology, Trondheim, Norway, Jun. 2018.
Z. Ye et al., “PQNTRU: Acceleration of NTRU-based schemes via customized post-quantum processor,” in IEEE Transactions on Computers, vol. 74, no. 5, pp. 1649–1662, May 2025.
J. Armakoon, U. Paracha, J. Iqbal, and M. A. Khan, “Post-quantum cryptography: From theory to practice,” Spectrum of Engineering Sciences, vol. 3, no. 5, pp. 892–918, May 2025.
X. Kai and Z. Yuxiang, “Improving the performance of 3D image model compression based on optimized DEFLATE algorithm,” Scientific Reports, vol. 14, Jun. 2024.
M. Ledwon, B. F. Cockburn and J. Han, “High-throughput FPGA-based hardware accelerators for deflate compression and decompression using high-level synthesis,” in IEEE Access, vol. 8, pp. 62207–62217, 2020.
W. Zhang, Y. Luo, X. Wang, J. Ouyang, L. Chen and F. An, “Dual-thread deflate/inflate accelerator with multicheckpoint control with high throughput and compression ratio for bandwidth-efficient systems,” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 33, no. 10, pp. 2761–2771, Oct. 2025.
Deeplumiere, “Patient clinical records readmission risk dataset: A synthetic Electronic Health Records (EHR) Dataset for clinical analytics, Kaggle. Jul. 07, 2026.
Queensland Government, “Koala Hospital Data—1996–2025,” Queensland Government Open Data Portal, Aug. 26, 2026.
