Abstract
The massive increase in smartphone devices capabilities have led to the development of mobile crowdsourcing applications (MCS). Many participants (individual workers) participates in performing different tasks, collecting data and sharing their work in a wide range of application areas. One of the most important issues in MCS applications is the privacy preservation for the participants, such as their identity and location. Most of the existing techniques and algorithms to protect the privacy of the participants focused on the identity or location as individual issues. However, in our research, we will implement an algorithm for protecting both the identity and location using RSA blind signature scheme to increase the privacy protection for the participants without using trusted third party. We demonstrated the efficiency of our approach to achieve the best performance in terms of reducing the communication overhead. Additionally, we approved our approach effectiveness in dealing with several attacks.
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This scientific paper contains studies and research results supported by King Abdulaziz City for Science and Technology, grant No. 1-17-00-009-0029.
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Albilali, A., Abulkhair, M. (2019). Worker’s Privacy Protection in Mobile Crowdsourcing Platform. In: Ahram, T., Nicholson, D. (eds) Advances in Human Factors in Cybersecurity. AHFE 2018. Advances in Intelligent Systems and Computing, vol 782. Springer, Cham. https://doi.org/10.1007/978-3-319-94782-2_16
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DOI: https://doi.org/10.1007/978-3-319-94782-2_16
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