PRISEC III: Dynamic Cryptographic Adaptation for Balancing Performance and Security

Authors

DOI:

https://doi.org/10.5753/jisa.2026.6502

Keywords:

Adaptive cryptography, IoT security, lightweight encryption, authenticated encryption, key management, post-quantum cryptography

Abstract

This paper introduces PRISEC III, a dynamic cryptographic framework designed to balance security and performance in heterogeneous IoT environments. Unlike static, one-size-fits-all approaches, PRISEC III employs a role-based multi-level model that adapts cryptographic strategies according to data sensitivity, device constraints, and network conditions. The framework integrates lightweight symmetric primitives for efficiency, robust asymmetric methods for secure key exchange, and hybrid schemes that combine multiple layers of protection. To enhance long-term resilience, PRISEC III also incorporates post-quantum options, ensuring preparedness against emerging cryptographic threats. Evaluation results demonstrate that the approach achieves scalable security while maintaining feasible computational costs, making it suitable for large-scale and resource-constrained IoT deployments.

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References

Aberna, P. and Agilandeeswari, L. (2025). Powbwm: Proof of work consensus cryptographic blockchain-based adaptive watermarking system. Alexandria Engineering Journal, 112:510-537. DOI: 10.1016/j.aej.2024.10.016.

Ahn, J., Hussain, R., Kang, K., and Son, J. (2025). Exploring encryption algorithms and network protocols: A comprehensive survey of threats and vulnerabilities. IEEE Communications Surveys & Tutorials. DOI: 10.1109/COMST.2025.3526605.

Aliabadi, F., Majidi, M., and Khorashadizadeh, S. (2022). Chaos synchronization using adaptive quantum neural networks and its application in secure communication and cryptography. Neural Computing and Applications, 34:6521-6533. DOI: 10.1007/s00521-021-06768-z.

Amrita, Ekwueme, C. P., Adam, I. H., and Dwivedi, A. (2024). Lightweight cryptography for internet of things: A review. EAI Endorsed Transactions on Internet of Things, 10. DOI: 10.4108/eetiot.5565.

Azar, K. Z., Kamali, H. M., Homayoun, H., and Sasan, A. (2021). From cryptography to logic locking: A survey on the architecture evolution of secure scan chains. IEEE Access, 9:73133-73151. DOI: 10.1109/ACCESS.2021.3080257.

Bhagat, V., Kumar, S., Gupta, S. K., and Chaube, M. K. (2023). Lightweight cryptographic algorithms based on different model architectures: A systematic review and futuristic applications. Concurrency and Computation: Practice and Experience, 35(10):e7425. DOI: 10.1002/cpe.7425.

Blackwood, A., Carrington, J., Baryshevsky, S., et al. (2024). The implementation of a hybrid large language model for adaptive cryptographic cyber defense. DOI: 10.21203/rs.3.rs-5120507/v1.

Brennaf, M. S., Yang, P., and Lanfranchi, V. (2025). Secured cost-effective anonymous federated learning with proxied privacy enhancement for personal devices. IEEE Internet of Things Journal, 12(15):29343-29353. DOI: 10.1109/JIOT.2025.3569200.

Costa, P. and Leithardt, V. (2024). Prisec ii - a comprehensive model for iot security: Cryptographic algorithms and cloud integration. Available at:[link].

de Juan-Iglesias, P., Gómez-Gómez, I., Barquero-Jimenez, C., Wilson, C. A., and Motrico, E. (2024). Effectiveness of online psychological interventions to prevent perinatal depression in fathers and non-birthing partners: A systematic review and meta-analysis of randomized controlled trials. Internet Interventions, 37. DOI: 10.1016/j.invent.2024.100759.

Dutta, I. K., Ghosh, B., and Bayoumi, M. A. (2019). Lightweight cryptography for internet of insecure things: A survey. In IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pages 475-481. DOI: 10.1109/CCWC.2019.8666557.

Farooq, A., Tariq, S., Amin, A., et al. (2024). Towards the design of new cryptographic algorithm and performance evaluation measures. Multimedia Tools and Applications, 83:9709-9759. DOI: 10.1007/s11042-023-15673-7.

Goyal, R., Pawar, A., Ravikumar, R., et al. (2024). A novel hybrid communication policy using network coding. Wireless Personal Communications. DOI: 10.1007/s11277-023-10854-x.

Hanchate, R. and Anandan, R. (2024). Medical image encryption using hybrid adaptive elliptic curve cryptography. IETE Journal of Research, 70(6):5734-5749. DOI: 10.1080/03772063.2023.2268578.

Khan, B. and Hashmi, A. (2025). Comparing crypto and digital cash systems: A cryptographic analysis. DOI: 10.36227/techrxiv.173627402.26411980/v1.

Kong, J. H., Ang, L.-M., and Seng, K. P. (2015). A comprehensive survey of modern symmetric cryptographic solutions for resource constrained environments. Journal of Network and Computer Applications, 49:15-50. DOI: 10.1016/j.jnca.2014.09.006.

Rivadeneira, J. E., Borges, G. A., Rodrigues, A., Boavida, F., and Silva, J. S. (2024). A unified privacy preserving model with ai at the edge for human-in-the-loop cyber-physical systems. Internet of Things, 25:101034. DOI: 10.1016/j.iot.2023.101034.

Rivadeneira, J. E., Silva, J. S., Colomo-Palacios, R., Rodrigues, A., and Boavida, F. (2023). User-centric privacy preserving models for a new era of the internet of things. Journal of Network and Computer Applications, 217. DOI: 10.1016/j.jnca.2023.103695.

Rubin, I. (2025). Networking security. In Principles of Data Transfer Through Communications Networks, the Internet, and Autonomous Mobiles, pages 671-684. IEEE. DOI: 10.1002/9781394267781.ch22.

Sanchez, O. T., Raposo, D., Rodrigues, A., Boavida, F., and Silva, J. S. (2023). Private lorawan network gateways: Assessment and monitoring in the context of iiot-based management. Engineering Proceedings, 47(1):4. DOI: 10.3390/engproc2023047004.

Saraiva, D. A. F., Leithardt, V. R. Q., de Paula, D., Mendes, A. S., González, G. V., and Crocker, P. (2019). Prisec: Comparison of symmetric key algorithms for iot devices. Sensors, 19(19):4312. DOI: 10.3390/s19194312.

Seok, B. and Lee, C. (2025). A novel approach to construct a good dataset for differential-neural cryptanalysis. IEEE Transactions on Dependable and Secure Computing, 22(1):246-262. DOI: 10.1109/TDSC.2024.3387662.

Shanks, G., Sterling, M., Harrington, N., et al. (2024). Innovative framework for ransomware detection using adaptive cryptographic behavior analysis. DOI: 10.36227/techrxiv.173214000.03491354/v1.

Silva, C., Cunha, V., Barraca, J., et al. (2024). Analysis of the cryptographic algorithms in iot communications. Information Systems Frontiers, 26:1243-1260. DOI: 10.1007/s10796-023-10383-9.

Thakor, V. A., Razzaque, M. A., and Khandaker, M. R. A. (2021). Lightweight cryptography algorithms for resource-constrained iot devices: A review, comparison and research opportunities. IEEE Access, 9:28177-28193. DOI: 10.1109/ACCESS.2021.3052867.

Wang, Z., Zhang, Z., Wang, Y., and Sun, R. (2025). An integrated evaluation framework of covert performance for lpi signals in iot security. IEEE Internet of Things Journal, 12(15):29860-29872. DOI: 10.1109/JIOT.2025.3569527.

Xu, B., Liu, Z., Zhu, H., Dong, B., Zhao, B., Yan, B., and Wei, J. (2025). A novel adversarial attack method for time-series regression models in iiot-based digital twins. IEEE Internet of Things Journal, 12(15):29278-29290. DOI: 10.1109/JIOT.2025.3569857.

Yuan, K., Huang, Y., Du, Z., et al. (2024). A multi-layer composite identification scheme of cryptographic algorithm based on hybrid random forest and logistic regression model. Complex & Intelligent Systems, 10:1131-1147. DOI: 10.1007/s40747-023-01212-2.

Zhang, C., Liang, Y., Tavares, A., Wang, L., Gomes, T., and Pinto, S. (2024). An improved public key cryptographic algorithm based on chebyshev polynomials and rsa. Symmetry, 16(3):263. DOI: 10.3390/sym16030263.

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Published

2026-05-23

How to Cite

Sohail, H., Noetzold, D., & Leithardt, V. R. Q. (2026). PRISEC III: Dynamic Cryptographic Adaptation for Balancing Performance and Security. Journal of Internet Services and Applications, 17(1), 174–191. https://doi.org/10.5753/jisa.2026.6502

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Section

Research article