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<p>Wireless sensor networks (WSNs) are increasingly being targeted by malicious users who abuse resource scarcity to mask attack origins, rendering traditional IP traceback methods inappropriate due to excessive latency, low accuracy, and unacceptable overhead. IP traceback in this paper is formulated as a quadratic unconstrained binary optimization (QUBO) problem, and quantum annealing is used via D-Wave hardware and hybrid solvers, and is integrated into an NS3 simulation environment. Comparative study with classical packet marking and probabilistic sampling regimes indicates that the quantum-enhanced model achieves 90% traceback success rates and 5–10 percentage point false positive reduction with comparable latency and energy expenses. These results affirm that cyberphysical and IoT domains can be significantly benefited by quantum annealing for attacker localization in WSNs, resulting in practical, low-overhead security solutions.</p>

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A quantum annealing-based approach for IP traceback in WSNs

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月20日

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  • Maxwell Antwi,
  • Franco Osei-Wusu,
  • William Asiedu,
  • Maxwell Barfi,
  • William A. Atuahene,
  • Siddique Abubakr Muntaka

摘要

Wireless sensor networks (WSNs) are increasingly being targeted by malicious users who abuse resource scarcity to mask attack origins, rendering traditional IP traceback methods inappropriate due to excessive latency, low accuracy, and unacceptable overhead. IP traceback in this paper is formulated as a quadratic unconstrained binary optimization (QUBO) problem, and quantum annealing is used via D-Wave hardware and hybrid solvers, and is integrated into an NS3 simulation environment. Comparative study with classical packet marking and probabilistic sampling regimes indicates that the quantum-enhanced model achieves 90% traceback success rates and 5–10 percentage point false positive reduction with comparable latency and energy expenses. These results affirm that cyberphysical and IoT domains can be significantly benefited by quantum annealing for attacker localization in WSNs, resulting in practical, low-overhead security solutions.