TARU PUBLICATIONS
Journal of Discrete Mathematical Sciences and Cryptography cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
submissions@tarupublications.com
Open Access Research Article

Secure routing in wireless networks using dominating sets

, * , , , ,

* Corresponding author · click or hover a name for details

pp. 4417–4428Vol. 29Issue 10-BOctober 2026DOI: 10.47974/JDMSC-3062 Crossmark XML
Received:
01 Apr 2026
Published Online:
31 Oct 2026
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-3062
Pages:
4417–4428

Abstract

Wireless networks, like wireless sensor networks (WSNs) and mobile ad hoc networks (MANETs), are an essential part of the modern communication systems and serve purposes, such as IoT, smart cities, and critical infrastructure monitors. Nevertheless, they are highly susceptible to security risks like blackhole, wormhole and Sybil attacks due to their decentralized and dynamic nature, and have energy efficiency and scalability problems. The current routing protocols are mainly concerned with performance or security improvement on a case-by-case basis which results in efficiency versus robustness trade-off. The present paper discusses this issue by suggesting a safe routing model that is founded on a trust-sensitive Connected Dominating Set (CDS). The aim of the research is to come up with a routing backbone that will reduce the communication overhead and at the same time increase resilience against malicious nodes. It uses a methodology that models the wireless network as a graph and defines the construction of CDS as an optimization problem with node trust, link reliability, and cost of communication. Secure CDO is built by a multi stage algorithm that includes node selection, pruning and connectivity enforcement that is followed by secure route discovery and lightweight encryption and authentication. Simulation-based performance assessment of the proposed method is done under different attack conditions and performance of the proposed method is compared with the traditional protocols like AODV, DSR and the current secure routing protocols. The findings indicate that the proposed framework attains a superior Packet Delivery Ratio (up to 98% in normal circumstances and much higher in attacks), a lower routing overhead (by an approximation of 30-40%), and a lower energy consumption with respect to the different sizes of the network.

Keywords

Subject Classifications

68M1868M12

References

[1] S. M. Abas, S. F. Noori, D. Yuvaraj, and S. S. Priya, “Quantum computing-inspired genetic algorithm for network optimization in WSN,” Int. J. Intell. Syst. Appl. Eng., vol. 12, pp. 188–194 (2024).

[2] C. Wang and B. Kang, “Air-ground collaborative networking for user-centric mobile following service in 6G,” Alexandria Eng. J., vol. 124, pp. 231–237 (2025), doi: 10.1016/j.aej.2025.03.132.

[3] A. Dinesh and J. Rangaraj, “An energy-efficient routing protocol for wireless body area networks using hybrid artificial bee colony optimization and chicken swarm optimization algorithm,” J. Eng. Appl. Sci., vol. 72, Art. no. 45 (2025), doi: 10.1186/s44147-024-00533-4.

[4] P. Kaur, D. Kaur, and R. Mahajan, “Wormhole attack detection technique in mobile ad hoc networks,” Wireless Pers. Commun., vol. 97, no. 2, pp. 2939–2950 (2017), doi: 10.1007/s11277-017-4643-z.

[5] O. Wardak, S. Kumar, and D. Sinha, “Encryption and decryption scheme through signed Cayley graph,” J. Discrete Math. Sci. Cryptogr., vol. 28, no. 7, pp. 2811–2825 (2025), doi: 10.47974/JDMSC-2201.

[6] X. Lv, S. Rani, S. Manimurugan, A. Slowik, and Y. Feng, “Quantum-inspired sensitive data measurement and secure transmission in 5G-enabled healthcare systems,” Tsinghua Sci. Technol., vol. 30, pp. 456–478 (2025).

[7] A. K. Sharma, N. Purohit, S. Joshi, I. U. Lakkewar, and P. Khobragade, “Securing IoT environments: Deep learning-based intrusion detection,” in Deep Learning for Intrusion Detection: Techniques and Applications. Hoboken, NJ, USA: Wiley, ch. 12, pp. 251–266 (2026), doi: 10.1002/9781394285198.ch12.

[8] A. Bashir, N. Farooq, A. Pervaiz, and A. H. Mir, “Security comparison of NTRU-Encrypt and ECC in smart healthcare systems,” J. Discrete Math. Sci. Cryptogr., vol. 29, no. 3, pp. 1249–1265 (2026), doi: 10.47974/JDMSC-2220.

[9] P. Nadanam, N. Kumaratharan, and M. A. Devi, “Innovative hybrid framework for routing and clustering in wireless sensor networks with quantum optimization,” Cybern. Syst., pp. 1–36 (2025).

[10] J. M. Clark, R. Andersson, and S. Moreau, “A comprehensive review of homomorphic commitment schemes for secure voting infrastructures: Security models, optimization techniques, and emerging computing applications,” Int. J. Adv. Comput. Eng. Commun. Technol., vol. 14, no. 2, pp. 190–198 (2025), doi: 10.65521/ijacect.v14i2.2081.

[11] R. Priyanka and D. K. Reddy, “GT-PSO—An approach for energy efficient routing in WSN,” Int. J. Comput. Sci. Netw. Secur., vol. 22, no. 1, pp. 17–26 (2022).

[12] V. Srinivasan, “Detection of black hole attack using honeypot agent-based scheme with deep learning technique on MANET,” Ingénierie des Systèmes d’Information, vol. 26, pp. 549–557 (2021).

[13] 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,” J. Inf. Optim. Sci., vol. 47, no. 5-A, pp. 1709–1717 (2026), doi: 10.47974/JIOS-2261.

Views: 5Downloads: 5Citations: 0