Declarative Privacy-Preserving Inference Queries
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909498363346944 |
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| author | Guan, Hong Tiwari, Ansh Gautier, Summer Ambrish, Rajan Hari Zhou, Lixi Wang, Yancheng Gupta, Deepti Yang, Yingzhen Xiao, Chaowei Chowdhury, Kanchan Zou, Jia |
| author_facet | Guan, Hong Tiwari, Ansh Gautier, Summer Ambrish, Rajan Hari Zhou, Lixi Wang, Yancheng Gupta, Deepti Yang, Yingzhen Xiao, Chaowei Chowdhury, Kanchan Zou, Jia |
| contents | Detecting inference queries running over personal attributes and protecting such queries from leaking individual information requires tremendous effort from practitioners. To tackle this problem, we propose an end-to-end workflow for automating privacy-preserving inference queries including the detection of subqueries that involve AI/ML model inferences on sensitive attributes. Our proposed novel declarative privacy-preserving workflow allows users to specify "what private information to protect" rather than "how to protect". Under the hood, the system automatically chooses privacy-preserving plans and hyper-parameters. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_12393 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Declarative Privacy-Preserving Inference Queries Guan, Hong Tiwari, Ansh Gautier, Summer Ambrish, Rajan Hari Zhou, Lixi Wang, Yancheng Gupta, Deepti Yang, Yingzhen Xiao, Chaowei Chowdhury, Kanchan Zou, Jia Databases Artificial Intelligence Detecting inference queries running over personal attributes and protecting such queries from leaking individual information requires tremendous effort from practitioners. To tackle this problem, we propose an end-to-end workflow for automating privacy-preserving inference queries including the detection of subqueries that involve AI/ML model inferences on sensitive attributes. Our proposed novel declarative privacy-preserving workflow allows users to specify "what private information to protect" rather than "how to protect". Under the hood, the system automatically chooses privacy-preserving plans and hyper-parameters. |
| title | Declarative Privacy-Preserving Inference Queries |
| topic | Databases Artificial Intelligence |
| url | https://arxiv.org/abs/2401.12393 |