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arXiv · 2401.12393

Declarative Privacy-Preserving Inference Queries

Hong Guan·Ansh Tiwari·Summer Gautier·Rajan Hari Ambrish·Lixi Zhou·Yancheng Wang·Deepti Gupta·Yingzhen Yang·Chaowei Xiao·Kanchan Chowdhury·Jia Zou
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Abstract

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.

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Hong Guan, Ansh Tiwari, Summer Gautier, Rajan Hari Ambrish, Lixi Zhou, Yancheng Wang, Deepti Gupta, Yingzhen Yang, Chaowei Xiao, Kanchan Chowdhury, Jia Zou. 2024-01-22. Declarative Privacy-Preserving Inference Queries. https://arxiv.org/abs/2401.12393

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