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Multi-Layered Open Data, Differential Privacy, and Secure Engineering: The Operational Framework for Environmental Digital Twins

Author

Listed:
  • Oleksandr Korchenko

    (Department of Computer Engineering and Cybersecurity, University of the National Education Commission, 2 Podchorazych St., 30-084 Krakow, Poland)

  • Anna Korchenko

    (Department of Computer Engineering and Cybersecurity, University of the National Education Commission, 2 Podchorazych St., 30-084 Krakow, Poland)

  • Dmytro Prokopovych-Tkachenko

    (Department of Cybersecurity and Information Technologies, University of Customs and Finance, 49000 Dnipro, Ukraine
    State Scientific Institution, Institute of Information, Security and Law of the National Academy of Legal Sciences of Ukraine, 01032 Kyiv, Ukraine)

  • Mikolaj Karpinski

    (Department of Software Engineering, University of the National Education Commission in Krakow, 2 Podchorazych St., 30-084 Krakow, Poland)

  • Svitlana Kazmirchuk

    (Department of Cybersecurity Systems and Technologies, State University of Information and Communication Technologies, 03110 Kyiv, Ukraine)

Abstract

Sustainable urban development increasingly relies on hyperlocal environmental analytics created by smart city platforms that combine stationary and mobile sensors, Earth observations, meteorology, and land-use data. However, accurate spatio-temporal resolution can provide indirect identification and amplify cybersecurity threats. This article proposes the regulatory and technical mapping that implements the General Data Protection Regulation (GDPR) and the Network and Information Security Directive (NIS2) throughout the lifecycle of environmental data—reception, transport, storage, analytics, sharing, and publication. The methods combine doctrinal legal analysis, a review of the scope of recent research, formalized compliance modeling, modeling with synthetic city-scale datasets, expert identification, and demonstration of integrated analytics. The demonstration links deep evaluation of neural abnormalities (convolutional plus recurrent layers), short-term Fourier transformation of sensor signals, byte-to-image telemetry fingerprints, and protocol event counters, thereby tracking detection to explanatory evidence and to control actions. Deliverables include a matrix aligning lifecycle stages with GDPR principles and rights, as well as with the responsibilities of NIS2; a checklist for assessing the impact on data protection, which takes into account the risks of fairness and stigmatization; a basic set of controls for identification and access, secure design, monitoring, continuity, supplier assurance, and incident reporting; as well as a multi-layered publishing strategy that combines transparency with privacy through aggregation, delayed release, differentiated privacy budgets, and research enclaves. The visualization confirms that technical signals can be included in audit-ready reporting and automated response, while the guidelines legally clarify the relevant bases for common use cases such as air quality assurance networks, noise mapping, citizen sensor applications, and mobility and exposure modeling. The effects of the policy emphasize shared services for small municipalities, supply chain security, and ongoing review to counteract the mosaic effect. Overall, the study shows how cities can maximize environmental and social value based on environmental data, while maintaining privacy, sustainability, and equity by design.

Suggested Citation

  • Oleksandr Korchenko & Anna Korchenko & Dmytro Prokopovych-Tkachenko & Mikolaj Karpinski & Svitlana Kazmirchuk, 2026. "Multi-Layered Open Data, Differential Privacy, and Secure Engineering: The Operational Framework for Environmental Digital Twins," Sustainability, MDPI, vol. 18(4), pages 1-34, February.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:4:p:1912-:d:1863466
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