Security In Energy-Harvesting Wireless Sensor Networks: Trojan and Replay Attack Detection Using Statistical Analysis
Location
Ada, Ohio
Start Date
9-12-2025 1:30 PM
End Date
9-12-2025 1:40 PM
Description
Energy-harvesting wireless sensor networks (EH-WSNs) enable long-term, self-sustaining monitoring by converting environmental energy into usable power. However, the limited and fluctuating energy supply makes conventional cryptographic protections impractical, leaving these networks vulnerable to lightweight but highly disruptive cyberattacks. This work investigates the security implications of two such threats—Burst Replay Attacks and Trojan Timing Attacks—within a single-hop TDMA-based EH-WSN. Using a hardware testbed of Arduino nodes equipped with XBee DigiMesh radios, we collect over 80,000 benign packets and an equal number of malicious packets for each attack scenario. Through statistical analysis of node uptime intervals, we find that simple metrics such as minimum interval duration and variance reliably distinguish malicious behavior across multiple attack intensities. Results show that Burst Replay Attacks significantly compress minimum intervals and alter variance profiles, while Trojan attacks introduce systematic timing drift detectable through similar indicators. These findings support the feasibility of a lightweight, statistics-based intrusion detection system suitable for power-constrained EH-WSNs. Future work includes expanding detection to multi-hop architectures and incorporating additional attack models.
Recommended Citation
Berei, Ethan, "Security In Energy-Harvesting Wireless Sensor Networks: Trojan and Replay Attack Detection Using Statistical Analysis" (2025). College of Engineering Student Research Colloquium. 9.
https://digitalcommons.onu.edu/eng_student_research_colloquium/2025/Presentations/9
Security In Energy-Harvesting Wireless Sensor Networks: Trojan and Replay Attack Detection Using Statistical Analysis
Ada, Ohio
Energy-harvesting wireless sensor networks (EH-WSNs) enable long-term, self-sustaining monitoring by converting environmental energy into usable power. However, the limited and fluctuating energy supply makes conventional cryptographic protections impractical, leaving these networks vulnerable to lightweight but highly disruptive cyberattacks. This work investigates the security implications of two such threats—Burst Replay Attacks and Trojan Timing Attacks—within a single-hop TDMA-based EH-WSN. Using a hardware testbed of Arduino nodes equipped with XBee DigiMesh radios, we collect over 80,000 benign packets and an equal number of malicious packets for each attack scenario. Through statistical analysis of node uptime intervals, we find that simple metrics such as minimum interval duration and variance reliably distinguish malicious behavior across multiple attack intensities. Results show that Burst Replay Attacks significantly compress minimum intervals and alter variance profiles, while Trojan attacks introduce systematic timing drift detectable through similar indicators. These findings support the feasibility of a lightweight, statistics-based intrusion detection system suitable for power-constrained EH-WSNs. Future work includes expanding detection to multi-hop architectures and incorporating additional attack models.