Evaluating the Usability of Differential Privacy Tools with Data Practitioners
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866913466190659584 |
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| author | Ngong, Ivoline C. Stenger, Brad Near, Joseph P. Feng, Yuanyuan |
| author_facet | Ngong, Ivoline C. Stenger, Brad Near, Joseph P. Feng, Yuanyuan |
| contents | Differential privacy (DP) has become the gold standard in privacy-preserving data analytics, but implementing it in real-world datasets and systems remains challenging. Recently developed DP tools aim to make DP implementation easier, but limited research has investigated these DP tools' usability. Through a usability study with 24 US data practitioners with varying prior DP knowledge, we evaluated the usability of four Python-based open-source DP tools: DiffPrivLib, Tumult Analytics, PipelineDP, and OpenDP. Our results suggest that using DP tools in this study may help DP novices better understand DP; that Application Programming Interface (API) design and documentation are vital for successful DP implementation; and that user satisfaction correlates with how well participants completed study tasks with these DP tools. We provide evidence-based recommendations to improve DP tools' usability to broaden DP adoption. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_13506 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Evaluating the Usability of Differential Privacy Tools with Data Practitioners Ngong, Ivoline C. Stenger, Brad Near, Joseph P. Feng, Yuanyuan Human-Computer Interaction Cryptography and Security Differential privacy (DP) has become the gold standard in privacy-preserving data analytics, but implementing it in real-world datasets and systems remains challenging. Recently developed DP tools aim to make DP implementation easier, but limited research has investigated these DP tools' usability. Through a usability study with 24 US data practitioners with varying prior DP knowledge, we evaluated the usability of four Python-based open-source DP tools: DiffPrivLib, Tumult Analytics, PipelineDP, and OpenDP. Our results suggest that using DP tools in this study may help DP novices better understand DP; that Application Programming Interface (API) design and documentation are vital for successful DP implementation; and that user satisfaction correlates with how well participants completed study tasks with these DP tools. We provide evidence-based recommendations to improve DP tools' usability to broaden DP adoption. |
| title | Evaluating the Usability of Differential Privacy Tools with Data Practitioners |
| topic | Human-Computer Interaction Cryptography and Security |
| url | https://arxiv.org/abs/2309.13506 |