Privacy and Security for Mobile Crowdsourcing
eBook - ePub

Privacy and Security for Mobile Crowdsourcing

  1. 124 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Privacy and Security for Mobile Crowdsourcing

About this book

This concise guide to mobile crowdsourcing and crowdsensing vulnerabilities and countermeasures walks readers through a series of examples, discussions, tables, initiative figures, and diagrams to present to them security and privacy foundations and applications. Discussed approaches help build intuition to apply these concepts to a broad range of system security domains toward dimensioning of next generations of mobiles crowdsensing applications. This book offers vigorous techniques as well as new insights for both beginners and seasoned professionals. It reflects on recent advances and research achievements.

Technical topics discussed in the book include but are not limited to:

  • Risks affecting crowdsensing platforms
  • Spatio-temporal privacy of crowdsourced applications
  • Differential privacy for data mining crowdsourcing
  • Blockchain-based crowdsourcing
  • Secure wireless mobile crowdsensing.

This book is accessible to readers in mobile computer/communication industries as well as academic staff and students in computer science, electrical engineering, telecommunication systems, business information systems, and crowdsourced mobile app developers.

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Yes, you can access Privacy and Security for Mobile Crowdsourcing by Shabnam Sodagari in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Cyber Security. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half Title Page
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Table of Contents
  7. Preface
  8. List of Figures
  9. List of Tables
  10. List of Abbreviations
  11. Introduction
  12. 1 The Importance of Crowdsourcing
  13. 2 Spatio-temporal Privacy of Crowdsourced Applications
  14. 3 Differentially Private Mobile Crowdsourcing
  15. 4 Trust in Edge- and Fog-based Vehicular Crowdsensing
  16. 5 Blockchain-based Solutions for Security and Privacy of MCS Systems
  17. 6 MCS Security Games and Incentive Mechanisms
  18. 7 Machine Learning Based Privacy/Security Solutions for MCS
  19. 8 Crowdsourced Mobile Apps
  20. 9 Reliable Industrial IoT using Crowdsourcing
  21. 10 Misinformation, Fake News, and Crowdsourcing
  22. 11 Security in 6G and Wi-Fi Communications Leveraging Mobile Crowdsensing
  23. Problems
  24. Index
  25. About the Author