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Measuring Engagement of Spectators of Social Digital Games
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Context Sensing System Analysis for Privacy Preservation Based on Game Theory.

Shengling Wang1, Luyun Li2, Weiman Sun3

  • 1College of Information Science and Technology, Beijing Normal University, Beijing 100875, China. wangshengling@bnu.edu.cn.

Sensors (Basel, Switzerland)
|February 18, 2017
PubMed
Summary
This summary is machine-generated.

This study uses game theory to analyze context sensing systems. A reputation mechanism and concern for future payoffs are key to ensuring user privacy and preventing data leaks.

Keywords:
context-awaregame theorymobile applicationprivacy protection

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Area of Science:

  • Computer Science
  • Game Theory
  • Cybersecurity

Background:

  • Context-aware applications on mobile phones offer personalized services based on user context.
  • Unreliable applications may leak user data to adversaries for profit, posing privacy risks.

Purpose of the Study:

  • To analyze the conditions under which users, applications, and adversaries in context sensing systems behave optimally.
  • To identify strategies for preserving user privacy and preventing unauthorized data acquisition.

Main Methods:

  • Game theory, specifically extensive form and repeated game models, was employed.
  • Analysis of single and multiple interaction scenarios involving three players: user, application, and adversary.
  • Determination of Nash equilibriums and cooperation conditions.

Main Results:

  • In single interactions, a reputation mechanism is vital for privacy preservation.
  • In multiple interactions, participants' concern for future payoffs significantly impacts system behavior.
  • Identified conditions for users to release context, applications to avoid leaking, and adversaries to refrain from retrieving context.

Conclusions:

  • Reputation mechanisms and future payoff considerations are critical for secure context sensing systems.
  • Game theory provides a framework for understanding and improving privacy in context-aware mobile applications.
  • The findings offer insights into designing more trustworthy and privacy-preserving context sensing systems.