Trustworthy Sensing for Public Safety in Cloud-Centric Internet of Things

The Internet of Things (IoT) paradigm stands for virtually interconnected objects that are identifiable and equipped with sensing, computing, and communication capabilities. Implementation of services and applications over the IoT architecture can take benefit of the cloud computing concept. Sensing-as-a-Service (S
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aaS) is a cloud-inspired service model which enables access to the IoT. In this paper, we present a framework where IoT can enhance public safety by crowd management via sensing services that are provided by smart phones equipped with various types of sensors. In order to ensure trustworthiness in the presented framework, we propose a reputation-based (S
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aaS) scheme, namely, Trustworthy Sensing for Crowd Management (TSCM) for front-end access to the IoT. TSCM collects sensing data based on a cloud model and an auction procedure which selects mobile devices for particular sensing tasks and determines the payments to the users of the mobile devices that provide data. Performance evaluation of TSCM shows that the impact of malicious users in the crowdsourced data can be degraded by 75% while trustworthiness of a malicious user converges to a value below 40% following few auctions. Moreover, we show that TSCM can enhance the utility of the public safety authority up to 85%.