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Article

Real-Time Detection and Response to Wormhole and Sinkhole Attacks in Wireless Sensor Networks

1
International Science Complex Astana, Astana 010000, Kazakhstan
2
Department of Information Systems, L.N. Gumilyov Eurasian National University, Astana 010000, Kazakhstan
3
Department of Mathematics, Computer Science, and Digital Forensics, Commonwealth University of Pennsylvania, Bloomsburg, PA 17815, USA
4
College of Computer and Systems Engineering, Abdullah Al Salem University, Khaldiya 72303, Kuwait
5
Department of Computer Science and Engineering, Yanbu Industrial College, Royal Commission for Jubail and Yanbu, Yanbu Industrial City 41912, Saudi Arabia
*
Author to whom correspondence should be addressed.
Technologies 2025, 13(8), 348; https://doi.org/10.3390/technologies13080348
Submission received: 1 June 2025 / Revised: 17 July 2025 / Accepted: 1 August 2025 / Published: 7 August 2025
(This article belongs to the Special Issue New Technologies for Sensors)

Abstract

Wireless sensor networks have become a vital technology that is extensively applied across multiple industries, including agriculture, industrial operations, and smart cities, as well as residential smart homes and environmental monitoring systems. Security threats emerge in these systems through hidden routing-level attacks such as Wormhole and Sinkhole attacks. The aim of this research was to develop a methodology for detecting security incidents in WSNs by conducting real-time analysis of Wormhole and Sinkhole attacks. Furthermore, the paper proposes a novel detection methodology combined with architectural enhancements to improve network robustness, measured by hop counts, delays, false data ratios, and route integrity. A real-time WSN infrastructure was developed using ZigBee and Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS) technologies. To realistically simulate Wormhole and Sinkhole attack scenarios and conduct evaluations, we developed a modular cyber–physical architecture that supports real-time monitoring, repeatability, and integration of ZigBee- and GSM/GPRS-based attacker nodes. During the experimentation, Wormhole attacks caused the hop count to decrease from 4 to 3, while the average delay increased by 40%, and false sensor readings were introduced in over 30% of cases. Additionally, Sinkhole attacks led to a 27% increase in traffic concentration at the malicious node, disrupting load balancing and route integrity. The proposed multi-stage methodology includes data collection, preprocessing, anomaly detection using the 3-sigma rule, and risk-based decision making. Simulation results demonstrated that the methodology successfully detected route shortening, packet loss, and data manipulation in real time. Thus, the integration of anomaly-based detection with ZigBee and GSM/GPRS enables a timely response to security threats in critical WSN deployments.
Keywords: WSNs; security incident detection; wormhole; sinkhole; ZigBee; GSM/GPRS WSNs; security incident detection; wormhole; sinkhole; ZigBee; GSM/GPRS

Share and Cite

MDPI and ACS Style

Zhukabayeva, T.; Zholshiyeva, L.; Mardenov, Y.; Buja, A.; Khan, S.; Alnazzawi, N. Real-Time Detection and Response to Wormhole and Sinkhole Attacks in Wireless Sensor Networks. Technologies 2025, 13, 348. https://doi.org/10.3390/technologies13080348

AMA Style

Zhukabayeva T, Zholshiyeva L, Mardenov Y, Buja A, Khan S, Alnazzawi N. Real-Time Detection and Response to Wormhole and Sinkhole Attacks in Wireless Sensor Networks. Technologies. 2025; 13(8):348. https://doi.org/10.3390/technologies13080348

Chicago/Turabian Style

Zhukabayeva, Tamara, Lazzat Zholshiyeva, Yerik Mardenov, Atdhe Buja, Shafiullah Khan, and Noha Alnazzawi. 2025. "Real-Time Detection and Response to Wormhole and Sinkhole Attacks in Wireless Sensor Networks" Technologies 13, no. 8: 348. https://doi.org/10.3390/technologies13080348

APA Style

Zhukabayeva, T., Zholshiyeva, L., Mardenov, Y., Buja, A., Khan, S., & Alnazzawi, N. (2025). Real-Time Detection and Response to Wormhole and Sinkhole Attacks in Wireless Sensor Networks. Technologies, 13(8), 348. https://doi.org/10.3390/technologies13080348

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