| Title | Smart Cities of Self-Determined Data Subjects |
|---|---|
| ID_Doc | 43441 |
| Authors | Frecé, JT; Selzam, T |
| Title | Smart Cities of Self-Determined Data Subjects |
| Year | 2017 |
| Published | |
| Abstract | Smart Cities depend on data from numerous different sources to live up to their full potential. Adding personal data from private sources to a smart city's resources significantly increases this potential. Sustainable utilisation of such data must base on legal compliancy, ethical soundness, and consent of the providing data subjects. They have to be assured that their personal data will not be used for anything beyond the scope they agreed to, and that it will not suffer from any additional risk exposure. For this we propose a solution for self-determined data subjects (SDDS), which keeps the private and personal data at their decentralized, safe locations, without depriving the smart city from the information contained within. SDDS achieves this with strict compartmentalization of its different system elements, by exclusively storing non-mnemonic indices and IDs in a public ledger, and by sending mere analytical results, yet no original data across the network. Such a setup ensures the data subjects' privacy, grants the smart city access to a high number of new data sources, and simultaneously handles the user-consent to ensure compliance with data protection laws. |
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