A secured routing algorithm for cluster-based networks, integrating trust-aware authentication mechanisms for energy-efficient and efficient data delivery
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.3.35Keywords:
Clustering, Optimal routing, Secured WSN, ECC, Data transmission, Energy consumption.Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Secure routing in Wireless Sensor Networks (WSNs) is vital for preserving data veracity and privacy in the face of possible threats. Traditional routing protocols lack robust security mechanisms, making WSNs vulnerable to attacks. Secure routing protocols in WSNs aim to address these vulnerabilities by implementing authentication, encryption, and intrusion detection techniques to ensure secure and reliable data transmission while minimizing energy consumption. This paper proposes a novel secured routing algorithm tailored for cluster-based networks, aimed at enhancing energy efficiency and data delivery security by integrating trust-based authentication mechanisms. The approach begins with the design of a clustering algorithm, which organizes network nodes into clusters based on proximity or network topology. Subsequently, a trust-based authentication mechanism is developed to evaluate the reliability and integrity of both nodes and links within the network. Building upon these foundational elements, a secured routing protocol is devised to capitalize on the cluster-based organization and trust-based authentication, thereby facilitating energy-efficient and secure data transmission. The proposed algorithm and authentication mechanism Cluster and Optimal Routing Assisted Cryptograph (CORAC) are implemented within a simulated network environment to validate their efficacy. Performance evaluation is conducted through simulation studies, focusing on key metrics such as packet delivery ratio, energy consumption, and security effectiveness. This comprehensive approach aims to address the dual challenges of energy efficiency and data security in cluster-based networks, offering a promising solution for future deployments in various applications.Abstract
How to Cite
Downloads
Similar Articles
- N. Saranya, M. Kalpana Devi, A. Mythili, Summia P. H, Data science and machine learning methods for detecting credit card fraud , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Avdhesh Kumar, Manoj Agarwal, Studies on challenges and opportunities for foreign direct investment in the automobile industry in India , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Pooja Soni, Vikramaditya Dave, Sujit Kumar, Hemani Paliwal, A comparative study of AI-driven techno-economic analysis for grid-tied solar PV-fuel cell hybrid power systems , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Amanda Q. Okronipa, Jones Y. Nyame, Adoption of health information systems in emerging economies: Evidence from Ghana , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- J. M. Aslam, K. M. Kumar, Enhancing security of cloud using static IP techniques , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Naveena Somasundaram, Vigneshkumar M, Sanjay R. Pawar, M. Amutha, Balu S, Priya V, AI-driven material design for tissue engineering a comprehensive approach integrating generative adversarial networks and high-throughput experimentation , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- A. Sathya, M. S. Mythili, MOHCOA: Multi-objective hermit crab optimization algorithm for feature selection in sentiment analysis of Covid-19 Twitter datasets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Swetha Rajkumar, Jayaprasanth Devakumar, LSTM based data driven fault detection and isolation in small modular reactors , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Nilesh M. Patil, P M. Krishna, G. Deena, C Harini, R.K. Gnanamurthy, Romala V. Srinivas, Exploring real-time patient monitoring and data analytics with IoT-based smart healthcare monitoring , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Olivia C. Gold, Jayasimman Lawrence, Enhanced LSTM for heart disease prediction in IoT-enabled smart healthcare systems , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
<< < 3 4 5 6 7 8 9 10 11 12 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- A. Rukmani, C. Jayanthi, Fuzzy optimization trust aware clustering approach for the detection of malicious node in the wireless sensor networks , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- V. Karthikeyan, C. Jayanthi, Advancements in image quality assessment: a comparative study of image processing and deep learning techniques , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Annalakshmi D., C. Jayanthi, An asymmetric key encryption and decryption model incorporating optimization techniques for enhanced security and efficiency , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- V. Karthikeyan, C. Jayanthi, Improving image quality assessment with enhanced denoising autoencoders and optimization methods , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- A. Rukmani, C. Jayanthi, Trust and security in wireless sensor networks: A literature review of approaches for malicious node detection , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper