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Programmer's Perception of Sensitive Information in Code.

Xinyao Ma1, Ambarish Gurjar1, Anesu Chaora1

  • 1Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Indiana, USA.

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This summary is machine-generated.

Developers struggle to consistently identify privacy-sensitive data in code. Increased technical expertise correlates with decreased consensus on data sensitivity, highlighting a need for better tools and practices.

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Area of Science:

  • Software Engineering
  • Information Security
  • Data Privacy

Background:

  • Global data protection regulations like GDPR and CCPA increase demands for data privacy.
  • Identifying privacy-sensitive information in code is crucial for compliance and security.

Purpose of the Study:

  • To investigate programmers' ability to discern data sensitivity in code.
  • To evaluate the accuracy, feasibility, and reliability of programmers in identifying sensitive variables.
  • To assess consensus among programmers regarding data sensitivity and the influence of expertise.

Main Methods:

  • An online card-sorting experiment was conducted with programmers of varying expertise levels.
  • Participants were asked to perceive the sensitivity of variable names in code snippets.
  • Analysis focused on accuracy, consensus, and the impact of security knowledge and expertise.

Main Results:

  • A significant lack of consistency was found in participants' perception of data processing sensitivity.
  • Divergence in opinions increased with higher technical expertise.
  • Consensus decreased across different categories of sensitive data as expertise grew.

Conclusions:

  • Programmers exhibit varying levels of privacy awareness regarding sensitive data in code.
  • Increased technical expertise does not necessarily lead to greater consensus on data sensitivity.
  • There is a clear need for improved industry practices and automated tools for sensitive data identification.