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Related Experiment Videos

Comprehensive quantitative analysis on privacy leak behavior.

Lejun Fan1, Yuanzhuo Wang, Xiaolong Jin

  • 1Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.

Plos One
|September 26, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces the first quantitative metrics for analyzing software privacy leak behavior. The new approach uses Privacy Petri Nets (PPN) to assess risks and compare different applications effectively.

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Area of Science:

  • Cyber Security
  • Software Engineering

Background:

  • Privacy information leaks are a significant cyber security concern, driven by malicious software providers.
  • Current methods for analyzing privacy leak behavior are limited to qualitative assessments, lacking quantitative rigor.

Purpose of the Study:

  • To introduce the first quantitative metrics for analyzing software privacy leak behavior.
  • To develop a comprehensive metric for comparing privacy leak risks across different software applications.

Main Methods:

  • Proposing four novel quantitative metrics: possibility, severity, crypticity, and manipulability.
  • Utilizing Privacy Petri Nets (PPN) as the foundational framework for analysis.
  • Developing an 'overall leak degree' metric for comparative analysis.

Main Results:

  • The proposed quantitative metrics effectively analyze privacy leak behavior in software.
  • The approach allows for a detailed, multi-faceted understanding of privacy risks.
  • Validation using real-world software confirms the effectiveness of the quantitative metrics.

Conclusions:

  • The developed quantitative approach fills a critical gap in privacy leak behavior analysis.
  • This method enables objective comparison and characterization of privacy risks in software.
  • The findings contribute to advancing cyber security by providing tools for robust privacy assessment.