Abstract
Participatory sensing is a revolutionary paradigm in which volunteers collect and share information from their local environment using mobile phones. Nevertheless, one of the most important issues and misgiving about participatory sensing applications is security. Different from other participatory sensing application challenges who consider user privacy and data trustworthiness, we consider network trustworthiness problem namely Sybil attacks in participatory sensing. Sybil attacks is a particularly harmful attack against participatory sensing application, where Sybil attacks focus on creating multiple online user identities called Sybil identities and try to achieve malicious results through these identities. In this paper, we proposed a Hybrid Trust Management (HTM) framework for detecting and analyze Sybil attacks in participatory sensing network. Our HTM was proposed for performing Sybil attack characteristic check and trustworthiness management system to verify coverage nodes in the participatory sensing. To verify the proposed framework, we are currently developing the proposed scheme on OMNeT++ network simulator in multiple scenarios to achieve Sybil identities detection in our simulation environment.
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Chang, SH., Tseng, KK., Cheng, SM. (2014). The Sybil Attack in Participatory Sensing: Detection and Analysis. In: Pan, JS., Snasel, V., Corchado, E., Abraham, A., Wang, SL. (eds) Intelligent Data analysis and its Applications, Volume I. Advances in Intelligent Systems and Computing, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-319-07776-5_30
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DOI: https://doi.org/10.1007/978-3-319-07776-5_30
Publisher Name: Springer, Cham
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