Performance truthfulness of differential privacy for db testing

HIGHLIGHTS

• What: In this the authors focus on one of these techniques namely differential privacy and examine its impact on benchmarking performance i.e. whether differential privacy can maintain the same performance characteristics as the original workload. The authors show that the performance of some queries (Q5, Q14, and Q15 for example) stays truthful to the original workload. In the experiments , the authors explored how customized pre-processing steps can mitigate these issues, however, these are often costly in practice due to an increase in end-to-end anonymization time. The authors have explored the performance truthfulness of . . .
  

   

  

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