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Related Experiment Video

Updated: Jan 20, 2026

Composite Scaffolds of Interfacial Polyelectrolyte Fibers for Temporally Controlled Release of Biomolecules
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ConTPL: Controlling Temporal Privacy Leakage in Differentially Private Continuous Data Release.

Yang Cao1, Li Xiong1, Masatoshi Yoshikawa2

  • 1Emory University, USA.

Proceedings of the VLDB Endowment. International Conference on Very Large Data Bases
|August 20, 2019
PubMed
Summary
This summary is machine-generated.

Temporal correlations in streaming data can unexpectedly increase privacy loss beyond the set epsilon. Our system, ConTPL, converts existing privacy mechanisms to bound this Temporal Privacy Leakage (TPL) for sensitive data streams.

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Area of Science:

  • Computer Science
  • Data Privacy
  • Cybersecurity

Background:

  • Real-world systems like the Internet of Things continuously collect sensitive data streams.
  • Existing ϵ-differential privacy mechanisms aim to control privacy loss but often overlook temporal correlations in data.
  • Temporal correlations can lead to privacy loss exceeding the intended bound, a phenomenon termed Temporal Privacy Leakage (TPL).

Purpose of the Study:

  • To address the issue of Temporal Privacy Leakage (TPL) in differentially private streaming data analysis.
  • To develop a system that automatically adapts existing privacy mechanisms to bound TPL.
  • To provide tools for understanding and visualizing the impact of TPL.

Main Methods:

  • Design and implementation of the ConTPL system.
  • Automatic conversion of existing differentially private streaming data release mechanisms.
  • Integration of interactive interfaces and real-time visualization for parameter exploration.

Main Results:

  • ConTPL successfully converts existing differentially private mechanisms to bound TPL.
  • The system allows data curators to explore the effects of various parameters on TPL.
  • Interactive visualization aids in understanding privacy loss dynamics in streaming data.

Conclusions:

  • Temporal correlations pose a significant challenge to differential privacy in streaming data.
  • ConTPL offers a practical solution to mitigate Temporal Privacy Leakage.
  • The system enhances the robustness of privacy protection for sensitive streaming data analysis.