A flexible privacy-preservation approach for IoT-driven smart Hospital employing diverse distribution methods
Internet-based connectivity is commonplace in the modern world. Among the many uses of the Internet of Things (IoT) aimed at improving the efficacy and efficiency of municipal management, smart Hospital figure prominently. Strong privacy protection measures are necessary since IoT devices in these s...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/16/e3sconf_icregcsd2025_03003.pdf |
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| Summary: | Internet-based connectivity is commonplace in the modern world. Among the many uses of the Internet of Things (IoT) aimed at improving the efficacy and efficiency of municipal management, smart Hospital figure prominently. Strong privacy protection measures are necessary since IoT devices in these smart Hospital frequently gather sensitive data. Enough privacy protection isn’t offered by the smart Hospital systems now in use. Differential Privacy-Preserving Smart Hospital (DP Smart Hospital) is a novel approach that we introduce to address this. DP Smart Hospital uses Laplace or exponential distributions in differential privacy strategies to protect sensitive data generated by IoT devices. After that, the altered data is delivered to a controller, which then sends it on to an Omada Software controller, the cloud, and finally another controller for more examination. Direct uploads of non-sensitive material to the cloud. Device privacy is difficult for adversaries to undermine in this dynamic privacy-preserving environment. Because the solution only adds 10–18% overhead to IoT devices, it is appropriate for devices that can handle this extra load. |
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| ISSN: | 2267-1242 |