Trust and security in wireless sensor networks: A literature review of approaches for malicious node detection
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.spl.40Keywords:
Wireless sensor network, Malicious node, Clustering approach, Efficient routing protocol.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.
Wireless sensor networks (WSNs) are widely used in various fields such as environmental monitoring, healthcare, military applications, and smart cities. However, due to their decentralized nature, limited resources, and deployment in often hostile environments, WSNs are vulnerable to several security threats, especially malicious node attacks. Malicious nodes can disrupt network operations by dropping packets, injecting false data, or launching attacks such as sinkholes, wormholes, and Sybil attacks. To counter these threats, numerous malicious node detection methods have been proposed, ranging from trust-based models to anomaly detection techniques and clustering-based approaches. In parallel, the design of efficient routing protocols plays a critical role in ensuring energy-efficient and secure data transmission within the network. This review paper presents a comprehensive analysis of existing techniques for malicious node detection and efficient routing in WSNsAbstract
How to Cite
Downloads
Similar Articles
- Bratati Dey, Poonam Sharma, A comprehensive review of urban growth studies and predictions using the Sleuth model , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Engida Admassu, Classifying enset based on their disease tolerance using deep learning , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Bhavya Sathenapalli, Kali Charan Sabat, Unleashing entrepreneurial spirit: Driving innovation and growth in a rapidly changing world , The Scientific Temper: Vol. 16 No. 06 (2025): The Scientific Temper
- Temesgen A. Asfaw, Deep learning hyperparameter’s impact on potato disease detection , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Deepa S, Sripriya T, Radhika M, Jeneetha J. J, Experimental evaluation of artificial intelligence assisted heart disease prediction using deep learning principle , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- S. Nagarani, Amalraj P., Lakshay Phor, Nishank S. Pimple, Banashree Sen, Ramaprasad Maiti, Vikas S. Jadhav, Innovative technological advancements in solving real quadratic equations: Pioneering the frontier of mathematical innovation , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Rupesh Mandal, Bobby Sharma, Dibyajyoti Chutia , Smart flood monitoring in Guwahati city: A LoRa-based AIoT and edge computing sensor framework , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- M. Menaha, J. Lavanya, Crop yield prediction in diverse environmental conditions using ensemble learning , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Gulshan Makkad, Lalsingh Khalsa, Vinod Varghese, Fractional thermoviscoelastic damping response in a non-simple micro-beam via DPL and KG nonlocality effect , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- Deepesh Bhardwaj, Niyati Chaudhary, Green Premium: Assessing the Influence of Sustainability Features on Real Estate Market Value in Delhi NCR , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
<< < 10 11 12 13 14 15 16 17 18 19 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Annalakshmi D, C. Jayanthi, A secured routing algorithm for cluster-based networks, integrating trust-aware authentication mechanisms for energy-efficient and efficient data delivery , The Scientific Temper: Vol. 15 No. 03 (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
- 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, Improving image quality assessment with enhanced denoising autoencoders and optimization methods , 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

