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Improved privacy preserving method for periodical SRS publishing.

Wei Huang1, Tong Yi2, Haibin Zhu3

  • 1Division of Scientific Research, Communication University of China, Beijing, China.

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New PPMS(k, θ, ɑ)-bounding enhances periodic adverse drug event data publication. This method protects sensitive patient information from medicine discontinuation and substantial symptom attacks, improving privacy without increasing data loss.

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Area of Science:

  • Pharmacovigilance
  • Data Privacy
  • Information Security

Background:

  • Spontaneous reporting systems (SRSs) collect adverse drug events (ADEs) crucial for drug safety monitoring.
  • Periodic publication of SRS data poses privacy risks, making sensitive information vulnerable to attacks like the Medicine Discontinuation (MD)-attack and Substantial Symptoms (SS)-attack.

Purpose of the Study:

  • To propose an improved periodical SRS data publishing method, PPMS(k, θ, ɑ)-bounding, to address existing vulnerabilities.
  • To enhance the privacy protection of published SRS data against specific data disclosure attacks.

Main Methods:

  • The PPMS(k, θ, ɑ)-bounding method incorporates a mechanism to ensure each equivalence group contains at least k new medicine discontinuation records, mitigating MD-attacks.
  • A heuristic algorithm is employed to thwart SS-attacks.

Main Results:

  • Theoretical analysis confirms PPMS(k, θ, ɑ)-bounding effectively thwarts MD-attacks and SS-attacks.
  • Experimental results show PPMS(k, θ, ɑ)-bounding offers superior privacy protection compared to existing methods.
  • The proposed method maintains information usability, ensuring released tables remain valuable for analysis.

Conclusions:

  • PPMS(k, θ, ɑ)-bounding significantly improves the privacy of published SRS data.
  • The method guarantees the usability of released data, balancing privacy with informational utility.
  • This advancement is vital for secure and effective pharmacovigilance data sharing.