A Reliable Hybrid Framework for Anomaly Detection in Secure and Robust Wireless Sensor Networks
Received: 14 April 2025 | Revised: 13 May 2025 | Accepted: 31 May 2025 | Online: 2 August 2025
Corresponding author: N. Raghavendra Sai
Abstract
The integration of the FireTG-Net model enables Firefly Swarm Optimization (FSO) to work with the Temporal-Gated Recurrent Unit-Network (Temporal-GRU-Net) for detecting anomalies in Wireless Sensor Networks (WSNs) resulting in 98.13% detection accuracy. The model employs FSO-optimized trust evaluation for local and global assessments that enables it to automatically adjust its detection methods to changing conditions and improve the efficiency of routing decisions. The model identifies immediate and changing malicious behaviors of blackhole, sinkhole, and jamming attacks through its 1D convolutional layers and advanced Gated Recurrent Units (GRUs) feature extraction capabilities. The FireTG-Net model exhibits superior evaluation scores compared to the Decision Tree (96%), Fuzzy Model (81%) and Trust-aware Routing Protocol (TRP) (96.791%) while facing disruptions better and showing restricted latency effects. FireTG-Net demonstrates excellent capabilities for enhancing the security and reliability of WSNs through its effective performance regarding high packet delivery ratio, enhanced energy efficiency, and reduced false positive rates.
Keywords:
wireless sensor networks, trust, FSO, anomaly detection optimization, GRUDownloads
References
N. Temene, C. Sergiou, C. Georgiou, and V. Vassiliou, "A Survey on Mobility in Wireless Sensor Networks," Ad Hoc Networks, vol. 125, Feb. 2022, Art. no. 102726. DOI: https://doi.org/10.1016/j.adhoc.2021.102726
H. Yang, X. Zhang, and F. Cheng, "A Novel Algorithm for Improving Malicious Node Detection Effect in Wireless Sensor Networks," Mobile Networks and Applications, vol. 26, no. 4, pp. 1564–1573, Aug. 2021. DOI: https://doi.org/10.1007/s11036-019-01492-4
A. Harbouche, D. Djabour, and A. Saiah, "Z-MSP: Zonal-Max Stable Protocol for Wireless Sensor Networks," Engineering, Technology & Applied Science Research, vol. 14, no. 6, pp. 18036–18041, Dec. 2024. DOI: https://doi.org/10.48084/etasr.8691
M. Huang, K. Zhang, Z. Zeng, T. Wang, and Y. Liu, "An AUV-Assisted Data Gathering Scheme Based on Clustering and Matrix Completion for Smart Ocean," IEEE Internet of Things Journal, vol. 7, no. 10, pp. 9904–9918, Oct. 2020. DOI: https://doi.org/10.1109/JIOT.2020.2988035
R. Liu, M. Xie, A. Liu, and H. Song, "Joint Optimization Risk Factor and Energy Consumption in IoT Networks With TinyML-Enabled Internet of UAVs," IEEE Internet of Things Journal, vol. 11, no. 12, pp. 20983–20994, Jun. 2024. DOI: https://doi.org/10.1109/JIOT.2023.3348837
N. Kumar and J.-H. Lee, "Peer-to-Peer Cooperative Caching for Data Dissemination in Urban Vehicular Communications," IEEE Systems Journal, vol. 8, no. 4, pp. 1136–1144, Dec. 2014. DOI: https://doi.org/10.1109/JSYST.2013.2285611
E. T. da Silva, A. L. D. Costa, and J. M. H. de Macedo, "On the realization of VANET using named data networking: On improvement of VANET using NDN-based routing, caching, and security," International Journal of Communication Systems, vol. 35, no. 18, Sep. 2022, Art. no. e5348. DOI: https://doi.org/10.1002/dac.5348
F. H. El-Fouly, M. Kachout, R. A. Ramadan, A. J. Alzahrani, J. S. Alshudukhi, and I. M. Alseadoon, "Energy-Efficient and Reliable Routing for Real-time Communication in Wireless Sensor Networks," Engineering, Technology & Applied Science Research, vol. 14, no. 3, pp. 13959–13966, Jun. 2024. DOI: https://doi.org/10.48084/etasr.7057
D. Manivannan, S. S. Moni, and S. Zeadally, "Secure authentication and privacy-preserving techniques in Vehicular Ad-hoc NETworks (VANETs)," Vehicular Communications, vol. 25, Oct. 2020, Art. no. 100247. DOI: https://doi.org/10.1016/j.vehcom.2020.100247
S. Mejjaouli and R. F. Babiceanu, "RFID-wireless sensor networks integration: Decision models and optimization of logistics systems operations," Journal of Manufacturing Systems, vol. 35, pp. 234–245, Apr. 2015. DOI: https://doi.org/10.1016/j.jmsy.2015.02.005
J. Zhang, X. Wang, B. Wang, W. Sun, H. Du, and Y. Zhao, "Energy-Efficient Data Transmission for Underwater Wireless Sensor Networks: A Novel Hierarchical Underwater Wireless Sensor Transmission Framework," Sensors, vol. 23, no. 12, Jun. 2023, Art. no. 5759. DOI: https://doi.org/10.3390/s23125759
F. Zijie, M. A. Al-Shareeda, M. A. Saare, S. Manickam, and S. Karuppayah, "Wireless sensor networks in the internet of things: review, techniques, challenges, and future directions," Indonesian Journal of Electrical Engineering and Computer Science, vol. 31, no. 2, pp. 1190–1200, Aug. 2023. DOI: https://doi.org/10.11591/ijeecs.v31.i2.pp1190-1200
D. Gangwani and P. Gangwani, "Applications of Machine Learning and Artificial Intelligence in Intelligent Transportation System: A Review," in Applications of Artificial Intelligence and Machine Learning: Select Proceedings of ICAAAIML 2020, Online, 2020, pp. 203–216. DOI: https://doi.org/10.1007/978-981-16-3067-5_16
J. Jiang, H. Wang, X. Mu, and S. Guan, "Logistics industry monitoring system based on wireless sensor network platform," Computer Communications, vol. 155, pp. 58–65, Apr. 2020. DOI: https://doi.org/10.1016/j.comcom.2020.03.016
Rekha and P. M. Sundaram, "Trust aware clustering approach for the detection of malicious nodes in the WSN," The Scientific Temper, vol. 15, no. spl-1, pp. 170–181, Oct. 2024. DOI: https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.spl.21
S. Shah et al., "A Dynamic Trust evaluation and update model using advance decision tree for underwater Wireless Sensor Networks," Scientific Reports, vol. 14, no. 1, Sep. 2024, Art. no. 22393. DOI: https://doi.org/10.1038/s41598-024-72775-4
B. P. Valluri and N. Sharma, "Trusted head node for Node Behaviour Analysis for malicious node detection in wireless sensor networks," Measurement: Sensors, vol. 36, Dec. 2024, Art. no. 101159. DOI: https://doi.org/10.1016/j.measen.2024.101159
C. Liu, J. Ye, F. An, and W. Jiang, "An Adaptive Trust Evaluation Model for Detecting Abnormal Nodes in Underwater Acoustic Sensor Networks," Sensors, vol. 24, no. 9, May 2024, Art. no. 2880. DOI: https://doi.org/10.3390/s24092880
M. Asha Rani and H. R. Roopashree, "Enhancing Wireless sensor network security with Trust-aware Routing protocol(TRP)Based on packet Forwarding Ratio Analysis to detect malicious nodes," in 2024 International Conference on Knowledge Engineering and Communication Systems, Chikkaballapur, India, 2024, vol. 1, pp. 1–7. DOI: https://doi.org/10.1109/ICKECS61492.2024.10616466
Downloads
How to Cite
License
Copyright (c) 2025 Gajjala Savithri, N. Raghavendra Sai
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
