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.
1. The Importance of Crowdsourcing
2. Spatio-temporal Privacy of Crowdsourced Applications
3. Differentially Private Mobile Crowdsourcing
4. Trust in Edge-and-fog-based Vehicular Crowdsensing
5. Blockchain-based Solutions for Security and Privacy of MCS Systems
6. MCS Security Games and Incentive Mechanisms
7. Machine Learning Based Privacy/Security Solutions for MCS 135
8. Crowdsourced Mobile Apps
9. Reliable Industrial IoT Using Crowdsourcing
10. Misinformation, Fake News, and Crowdsourcing
11. Security in 6G and Wi-Fi Communications Leveraging
Mobile Crowdsensing
12. Problems
Biography
Shabnam Sodagari received her Ph.D. from the Pennsylvania State University in electrical engineering and is a faculty member of computer engineering and computer science.
