0000000000638171

AUTHOR

Timothy S. Sanders

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FIRST

2018

Thanks to the collective action of participating smartphone users, mobile crowdsensing allows data collection at a scale and pace that was once impossible. The biggest challenge to overcome in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior, thus compromising the accuracy of the data collection process. Therefore, it becomes imperative to design algorithms to accurately classify between reliable and unreliable sensing reports. To address this crucial issue, we propose a novel Framework for optimizing Information Reliability in Smartphone-based participaTory sensing (FIRST) that leverages mobile trusted participants (MTPs) to securely assess the reliabil…

FOS: Computer and information sciencesComputer Networks and CommunicationsComputer scienceDistributed computingFrameworkCrowdsensing02 engineering and technologyTrustMobileComputer Science - Networking and Internet ArchitectureThe National MapInformation020204 information systems0202 electrical engineering electronic engineering information engineeringAndroid (operating system)ReputationPaceSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniNetworking and Internet Architecture (cs.NI)Data collectionParticipatory sensingInformation quality020206 networking & telecommunicationsQualitySoftware deploymentWireless sensor networkACM Transactions on Sensor Networks
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