Position: GDPR Compliance by Construction
© 2019, Springer Nature Switzerland AG. New laws such as the European Union’s General Data Protection Regulation (GDPR) grant users unprecedented control over personal data stored and processed by businesses. Compliance can require expensive manual labor or retrofitting of existing systems, e.g., to...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer International Publishing
2021
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| Online Access: | https://hdl.handle.net/1721.1/132311 |
| _version_ | 1826197989505368064 |
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| author | Schwarzkopf, Malte Kohler, Eddie Frans Kaashoek, M Morris, Robert |
| author_facet | Schwarzkopf, Malte Kohler, Eddie Frans Kaashoek, M Morris, Robert |
| author_sort | Schwarzkopf, Malte |
| collection | MIT |
| description | © 2019, Springer Nature Switzerland AG. New laws such as the European Union’s General Data Protection Regulation (GDPR) grant users unprecedented control over personal data stored and processed by businesses. Compliance can require expensive manual labor or retrofitting of existing systems, e.g., to handle data retrieval and removal requests. We argue for treating these new requirements as an opportunity for new system designs. These designs should make data ownership a first-class concern and achieve compliance with privacy legislation by construction. A compliant-by-construction system could build a shared database, with similar performance as current systems, from personal databases that let users contribute, audit, retrieve, and remove their personal data through easy-to-understand APIs. Realizing compliant-by-construction systems requires new cross-cutting abstractions that make data dependencies explicit and that augment classic data processing pipelines with ownership information. We suggest what such abstractions might look like, and highlight existing technologies that we believe make compliant-by-construction systems feasible today. We believe that progress towards such systems is at hand, and highlight challenges for researchers to address to make them a reality. |
| first_indexed | 2024-09-23T10:57:08Z |
| format | Article |
| id | mit-1721.1/132311 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:57:08Z |
| publishDate | 2021 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1323112021-09-21T03:46:08Z Position: GDPR Compliance by Construction Schwarzkopf, Malte Kohler, Eddie Frans Kaashoek, M Morris, Robert © 2019, Springer Nature Switzerland AG. New laws such as the European Union’s General Data Protection Regulation (GDPR) grant users unprecedented control over personal data stored and processed by businesses. Compliance can require expensive manual labor or retrofitting of existing systems, e.g., to handle data retrieval and removal requests. We argue for treating these new requirements as an opportunity for new system designs. These designs should make data ownership a first-class concern and achieve compliance with privacy legislation by construction. A compliant-by-construction system could build a shared database, with similar performance as current systems, from personal databases that let users contribute, audit, retrieve, and remove their personal data through easy-to-understand APIs. Realizing compliant-by-construction systems requires new cross-cutting abstractions that make data dependencies explicit and that augment classic data processing pipelines with ownership information. We suggest what such abstractions might look like, and highlight existing technologies that we believe make compliant-by-construction systems feasible today. We believe that progress towards such systems is at hand, and highlight challenges for researchers to address to make them a reality. 2021-09-20T18:21:47Z 2021-09-20T18:21:47Z 2020-12-22T14:22:58Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/132311 en 10.1007/978-3-030-33752-0_3 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Springer International Publishing MIT web domain |
| spellingShingle | Schwarzkopf, Malte Kohler, Eddie Frans Kaashoek, M Morris, Robert Position: GDPR Compliance by Construction |
| title | Position: GDPR Compliance by Construction |
| title_full | Position: GDPR Compliance by Construction |
| title_fullStr | Position: GDPR Compliance by Construction |
| title_full_unstemmed | Position: GDPR Compliance by Construction |
| title_short | Position: GDPR Compliance by Construction |
| title_sort | position gdpr compliance by construction |
| url | https://hdl.handle.net/1721.1/132311 |
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