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Differential Privacy for Coverage Analysis of Software Traces (Artifact)

Authors Yu Hao, Sufian Latif, Hailong Zhang, Raef Bassily, Atanas Rountev



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DARTS.7.2.7.pdf
  • Filesize: 413 kB
  • 3 pages

Document Identifiers

Author Details

Yu Hao
  • Ohio State University, Columbus, OH, USA
Sufian Latif
  • Ohio State University, Columbus, OH, USA
Hailong Zhang
  • Fordham University, New York, NY, USA
Raef Bassily
  • Ohio State University, Columbus, OH, USA
Atanas Rountev
  • Ohio State University, Columbus, OH, USA

Acknowledgements

We thank the ECOOP artifact reviewers for their valuable feedback and the artifact co-chairs for their help.

Cite AsGet BibTex

Yu Hao, Sufian Latif, Hailong Zhang, Raef Bassily, and Atanas Rountev. Differential Privacy for Coverage Analysis of Software Traces (Artifact). In Special Issue of the 35th European Conference on Object-Oriented Programming (ECOOP 2021). Dagstuhl Artifacts Series (DARTS), Volume 7, Issue 2, pp. 7:1-7:3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/DARTS.7.2.7

Artifact

Abstract

We propose a differentially private coverage analysis for software traces. To demonstrate that it achieves low error and high precision while preserving privacy, we evaluate the analysis on simulated traces for 15 Android apps. The open source implementation of the analysis, which is in Java, and the dataset used in the experiments are released as an artifact. We also provide specific guidance on reproducing the experimental results.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Dynamic analysis
  • Security and privacy → Privacy-preserving protocols
Keywords
  • Trace Profiling
  • Differential Privacy
  • Program Analysis

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