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Privacy-Enhanced Database Synthesis for Benchmark Publishing
May 3, 2024, 4:15 a.m. | Yongrui Zhong, Yunqing Ge, Jianbin Qin, Shuyuan Zheng, Bo Tang, Yu-Xuan Qiu, Rui Mao, Ye Yuan, Makoto Onizuka, Chuan Xiao
cs.CR updates on arXiv.org arxiv.org
Abstract: Benchmarking is crucial for evaluating a DBMS, yet existing benchmarks often fail to reflect the varied nature of user workloads. As a result, there is increasing momentum toward creating databases that incorporate real-world user data to more accurately mirror business environments. However, privacy concerns deter users from directly sharing their data, underscoring the importance of creating synthesized databases for benchmarking that also prioritize privacy protection. Differential privacy has become a key method for safeguarding privacy …
arxiv benchmark benchmarking benchmarks business cs.cr cs.db data database databases environments fail mirror momentum nature privacy privacy concerns publishing real result sharing user data workloads world
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