Abstract
Mobile crowdsensing is a powerful paradigm that exploits the advanced sensing capabilities and ubiquity of smartphones in order to collect and analyze data on a scale that is impossible with fixed sensor networks. Mobile crowdsensing systems incorporate people and rely on their participation and willingness to contribute up-to-date and accurate information, meaning that such systems are prone to malicious and erroneous data. Therefore, trust and reputation are key factors that need to be addressed in order to ensure sustainability of mobile crowdsensing systems. The objective of this work is to define the conceptual trust framework that considers human involvement in mobile crowdsensing systems and takes into account that users contribute their opinions and other subjective data besides the raw sensing data generated by their smart devices. We propose a novel method to evaluate the trustworthiness of data contributed by users that also considers the subjectivity in the contributed data. The method is based on a comparison of users’ trust attitudes and applies nonparametric statistic methods. We have evaluated the performance of our method with extensive simulations and compared it to the method proposed by Huang that adopts Gompertz function for rating the contributions. The simulation results showed that our method outperforms Huang’s method by 28.6% on average and the method without data trustworthiness calculation by 33.6% on average in different simulation settings.
Highlights
Smartphones and other smart devices have become an influential part of our everyday lives and one of the most powerful pervasive technologies
The objective of this work is to define a conceptual trust framework that considers human involvement in mobile crowdsensing systems and takes into account that users contribute their opinions and other subjective data besides the raw sensing data generated by their smart devices
In the previous section we described our conceptual trust framework for mobile crowdsensing systems and a novel method to evaluate the trustworthiness of participants’ contributions
Summary
Smartphones and other smart devices have become an influential part of our everyday lives and one of the most powerful pervasive technologies. Around 60 percent of all mobile phone subscriptions are associated with smartphones, wherein each active smartphone has, on average, 3.4 GB monthly data traffic. Advanced sensing capabilities and the ubiquity of smart devices are the basis for the mobile crowdsensing paradigm. Mobile crowdsensing systems employ ordinary users (or citizens) to collect, monitor, process, store and share large amounts of data [2,3]. It extends participatory sensing approach with implicit data contribution and data extraction from other widely used applications [4]. User-generated content include opinions or experiences, which add knowledge
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