Utility of Differentially Private Synthetic Data Generation for High-Dimensional Databases
When processing data that contains sensitive information, careful consideration is required with regard to privacy-preservation to prevent disclosure of confidential information. Privacy engineering enables one to extract valuable patterns, safely, without compromising anyone’s privacy. Over the las...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2018
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-237424 |