{"id":11174,"date":"2026-08-26T21:39:44","date_gmt":"2026-08-26T13:39:44","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=11174"},"modified":"2026-08-26T23:16:25","modified_gmt":"2026-08-26T15:16:25","slug":"jase-202612-35-010","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202612-35-010","title":{"rendered":"Data Privacy Protection and Secure Transmission Strategies for Distributed Sensor Networks in Urban Water Environment Monitoring"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 35<\/a><\/p>\n<\/div>\n\n\n\n

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Ning Zhang and Tianchu Shu<\/i><\/a><\/p>\n\n\n\n

Ecological Municipal Institute, CAUPD Beijing Planning and Design consultants LTD, Haidian 100044, Beijing, China<\/p>\n<\/div>\n\n\n\n

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Received: July 21, 2026
Accepted: August 08, 2026
Publication Date: August 26, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

SPST-WSN Overall Architecture<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation: BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202612_35.010<\/a> <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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Urban water environment monitoring relies on large-scale distributed sensor networks continuously collecting multi-source water quality data – pH, dissolved oxygen, turbidity, COD, ammonia nitrogen, and temperature. High-density node access, edge-gateway forwarding, and centralized cloud analysis expose these systems to data leakage, node spoofing, eavesdropping, replay, tampering, and inference of sensitive patterns, and a single encrypted channel cannot satisfy privacy, security, and scalability together. This study proposes SPST-WSN, a scalable privacy-preserving secure transmission framework integrating adaptive differential privacy, lightweight encryption, dynamic session-key updates, timestamp\/nonce verification, MAC-based integrity verification, and link-risk-aware routing across sensor nodes, edge gateways, secure routing, and a cloud platform. In simulations, as node scale grows from 100 to 1500, latency reaches about 168 ms-43.8% lower than blockchain-based methods. with throughput above 760 packets\/s. Under 30% attack intensity, delivery rate remains 92.4%, privacy leakage risk falls to 0.18 at budget 0.5, and detection rates for tampering, replay, and spoofing reach 96.8%, 95.9%, and 94.7%. SPST-WSN improves privacy, security, anomaly detection, and scalability while preserving utility for urban rivers, outfalls, lakes, and pipe networks.<\/p>\n\n\n\n

Keywords: Urban water environment monitoring, distributed sensor network, privacy protection, secure transmission, edge computing, differential privacy, scalable information system<\/em><\/p>\n\n\n\n

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