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May 6, 2026Sensors1 citationsOpen Access

Blockchain-Enabled Uncertainty-Aware Passive Wi-Fi Localization for Secure Critical Infrastructure Sensor Networks

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DPDmytro Prokopovych-TkachenkoOGOleksandr GalushchenkoОТОльга Торстенссон

Key Points

  • The aim is to develop a framework for reliable passive Wi-Fi localization in critical infrastructure using uncertainty calibration.
  • Developed a Bayesian coordinate estimation technique utilizing robust loss functions.
  • Implemented uncertainty calibration for operational SOC response modes.
  • Established an evidentiary logging layer for on-chain metadata integrity.
  • Validated the localization framework's performance with strict SOC operational boundaries.
  • Field tests indicated marked performance degradation beyond 40 m for reliable automation.
  • Integrated components enhance security and auditability in sensor networks.

Abstract

Passive Wi-Fi localization for critical-infrastructure security operations centers (SOCs) faces three interconnected limitations. First, many existing methods produce single-point coordinate estimates without calibrated uncertainty, making them unsuitable for automated SOC response. Second, localization pipelines often lack an evidentiary chain of custody, limiting reliable post-incident auditability. Third, SOC automation cannot safely rely on uncalibrated confidence values because erroneous high-impact actions and missed escalations carry asymmetric operational costs. This study presents a Blockchain-Enabled Uncertainty-Aware Passive Wi-Fi Localization framework for heterogeneous sensor networks composed of stationary sensors, mobile receivers, and UAV-assisted collection nodes. Instead of producing a single coordinate estimate, the method derives a posterior spatial distribution with calibrated uncertainty from monitor-mode observations, including RSSI aggregates, management/control frame features, channel occupancy indicators, and receiver logs. The framework combines three tightly coupled components: (i) Bayesian coordinate estimation with robust loss functions and range-dependent error modeling; (ii) uncertainty calibration that converts posterior confidence into operational SOC response modes (AUTO, VERIFY, and OBSERVE) via empirical coverage metrics and reliability diagrams; and (iii) a permissioned evidentiary logging layer that anchors integrity-relevant metadata and policy labels on-chain while keeping raw telemetry off-chain for tamper-evident auditability and scalability. The coupling between layers is explicit: calibrated confidence scores govern smart-contract gating conditions, and smart-contract policy thresholds feed back into the calibration stage. Field validation shows that localization performance degrades markedly beyond approximately 40 m, indicating a practical boundary for confident automated action. The proposed framework integrates passive sensing, uncertainty-aware localization, and blockchain-based evidentiary trust for secure critical-infrastructure sensor networks. Its key contributions are: (1) a posterior-distribution-based passive localization pipeline; (2) empirical coverage metrics for calibrating SOC response thresholds; (3) a hybrid on-chain/off-chain architecture linking localization outputs to a permissioned ledger; and (4) field validation establishing the 40 m operational validity boundary.

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Cite This Study

Prokopovych-Tkachenko et al. (2026) studied this question.

synapsesocial.com/papers/69faa1eb04f884e66b5329f1https://doi.org/10.3390/s26092797
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